A system for making a diagnosis via artificial intelligence by processing hospital data through 5g and beyond networks

Abstract

The present invention relates to a system which collects data gathered by means of loT technology such as tests, diagnoses and other examinations in hospitals and also data obtained by means of a standardized form -that is filled in by patients and doctors- in a fast and low-latency way by using edge computing and network virtualization technology and which enables to make a diagnosis via artificial intelligence by processing this data through 5G and beyond network technology.

Description

[0001] A SYSTEM FOR MAKING A DIAGNOSIS VIA ARTIFICIAL

[0002] INTELLIGENCE BY PROCESSING HOSPITAL DATA THROUGH 5G AND BEYOND NETWORKS

[0003] Technical Field

[0004] The present invention relates to a system for collecting tests, diagnoses and other examinations in hospitals by means of standardized forms, and making a diagnosis via artificial intelligence by processing this data through 5G and beyond networks.

[0005] Background of the Invention

[0006] Today, data sharing is considered as a critical infrastructure for hospitals since it is an important parameter for patient diagnosis, treatment and follow-up. Today, hospitals try to solve this problem by using their own data centers and servers. However, this solution does not solve critical problems such as the shortage of doctors in the increasing patient density observed during the pandemic period and as well as the inadequacy of the technological infrastructure to integrate nextgeneration solutions such as artificial intelligence into the hospital infrastructure.

[0007] Therefore, considering the studies and the shortcomings included in the current technique, it is understood that there is need for a system which enables to create an advanced analysis output close to the final diagnosis in order to guide the doctor in diagnosis and treatment by handling patients’ histories, analyzes and diagnoses in different departments and their current conditions in an end-to-end way via different artificial intelligence and data learning techniques; to provide a more advanced and higher capacity for all purposes such as data storage, machine learning computations, data transfer and communication through the use of beyond 5G and 6G technologic; to include many different artificial intelligence and deep learning models -wherin each model may be different for different health data- into the diagnosis with different layers, by taking them into account; and to offer much more customized diagnosis and treatment options for various health conditions.

[0008] The Chinese patent document no. CN115798662A, an application included in the state of the art, discloses a system which enables to make healthcare services faster and more efficient by transmitting the data collected by measuring devices about the patient, to specialists and treatment devices by using 5G and Internet of Things technologies. The invention provides a case delivery analysis system for hospital case management based on an artificial intelligence algorithm. The system is characterized in that the data of each medical diagnosis and treatment device is collected by a 5G Internet of Things terminal data collection device connected to the device. The medical diagnosis and treatment device, and the 5G Internet of Things terminal data collection device transmits the data to a medical institution to which the 5G Internet of Things terminal data collection device belongs through a 5G base station; the medical institution uploads the data to the cloud server through the Internet; and the medical record transportation analysis system for hospital medical record management in the cloud server processes the data; the medical record delivery analysis system for hospital medical record management comprises a plurality of modules. The artificial intelligence algorithm is a neighbor algorithm. According to the invention, the medical record of the patient is changed from paper to electronization and informatization, and the medical efficiency and the medical quality are improved.

[0009] Summary of the Invention

[0010] An objective of the present invention is to realize a system which is developed for collecting tests, diagnoses and other examinations in hospitals by means of standardized forms, and making a diagnosis via artificial intelligence by processing this data through 5G and beyond networks.

[0011] Another objective of the present invention is to realize a system which is developed for collecting and securely storing patient data through Internet of Things (loT) technology and sensors, and providing better diagnosis and treatment recommendations to patients by nalyzing this data via artificial intelligence modules.

[0012] Another objective of the present invention is to realize a system which is developed for developing a holistic platform by using analyses from different departments in a mutually supportive manner and integrating patient history into the diagnosis, and thus assisting doctors in diagnosis and treatment.

[0013] Another objective of the present invention is to realize a system which is developed for recording patients’ health data in an orderly and consistent manner, providing better diagnoses and treatment recommendations and enabling patients to receive better and personalized health services, by means of standardized diagnosis cards.

[0014] Another objective of the present invention is to realize a system which is developed for processing of large amounts of health data in a fast and reliable way, taking medical decisions faster and treating patients faster, through 5G and beyond networks.

[0015] Another objective of the present invention is to realize a system which is developed for analyzing patients’ data through artificial intelligence modules and then making more precise diagnoses and providing more effective treatment recommendations, supporting the decision-making processes of healthcare professionals, to improving patient outcomes. Another objective of the present invention is to realize a system which is developed for making hospital management more productive, using resources better and planning of healthcare services better, by providing feeding of different diagnostic methods and and data integration.

[0016] Detailed Description of the Invention

[0017] “A System for Making a Diagnosis via Artificial Intelligence by Processing Hospital Data through 5G and Beyond Networks” realized to fulfil the objectives of the present invention is shown in the figure attached, in which:

[0018] Figure l is a schematic view of the inventive system.

[0019] The components illustrated in the figure are individually numbered, where the numbers refer to the following:

[0020] 1. System

[0021] 2. Visual Measurement Device

[0022] 3. Sensor Device

[0023] 4. loT Devices Management Server

[0024] 5. Network Functions Virtualization Server

[0025] 6. User Interface Server

[0026] 7. Data Storage Server

[0027] 8. Security Server

[0028] 9. Artificial Intelligence Server

[0029] 10. Visual Processing Server

[0030] 11. Digital Processing Server

[0031] 12. Natural Language Processing Server

[0032] 13. Time-Sequenced Relationship Processing Server

[0033] 14. Training and Improvement Server

[0034] 15. Integration Server 16. Legal and Ethical Compliance Server

[0035] HE. Patient Electronic Device

[0036] SE. Healthcare Worker Electronic Device

[0037] The inventive system (1) for collecting tests, diagnoses and other examinations in hospitals by means of standardized forms and making a diagnosis via artificial intelligence by processing this data through 5G and beyond networks; comprises at least one visual measurement device (2) which is configured to produce imaging results and to capture the medical data received from patients;

[0038] - at least one sensor device (3) which is configured to comprise measuring devices such as blood test sensors and pulse meters and to capture the medical data received from patients;

[0039] - at least one loT devices management server (4) which is configured to establish connection with the visual measurement device (2) and the sensor device (3) and to access the data thereon by using any communication protocol; to ensure data transfer and management in a coordinated way; and to transfer the collected data to other servers over the mobile network;

[0040] - at least one network functions virtualization server (5) which is configured establish connection with the loT devices management server (4) by using any communication protocol; to access the data transmitted by the loT devices management server (4) over the mobile network; to ensure that the data transmitted by the loT devices management server (4) is transported to other servers through the core network which is responsible for managing virtual functions in 5G and beyond networks; to be built on edge computing technology; to ensure data processing, data transfer, data integration and data management by hosting specialized virtual functions; to scale data processing together with virtualization technology of network functions and to run more functions according to need; to provide fast, scalable, low-latency service with virtualization technology of network functions; to use specialized virtual network functions in order to provide the data needed by artificial intelligence models quickly;

[0041] - at least one user interface server (6) which is configured to establish connection with the patient electronic device (HE) and health worker electronic device (SE) by using any communication protocol; to access data; to enable patients to view, control and manage their data over the patient electronic device (HE); to enable healthcare workers to view, update the patients’ information, to manage permissions and to track patients over the healthcare worker electronic device (SE); to arrange and manage permits; to produce and keep record of patient forms, diagnosis forms and treatment forms that are standardized therein and can be filled in by healthcare professionals and patients;

[0042] - at least one data storage server (7) which is configured to establish connection with the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by using any communication protocol; to access and to keep record of the data thereon; and to keep record of patient and healthcare worker information;

[0043] - at least one security server (8) which is configured to establish connection with the data storage server (7) by using any communication protocol and to implement security measures in order to prevent patient information from falling into the hands of unintended persons;

[0044] - at least one artificial intelligence server (9) which is configured to access the data on the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by establishing connection with the security server (8) by using any communication protocol; to include specialized servers according to the type of data; to process and analyze the data in a systematic way; to access all processed data and to combine it in a unifying layer; to form a single vector thereof; to process this vector containing the combined data in an output model by using deep neural networks; and to generate diagnosis and treatment recommendations by generating results; - at least one visual processing server (10) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process the images displayed through the visual measurement device (2); and to run visual processing-based deep learning models in the form of convolutional neural networks on these images; to analyze the images and to produce results;

[0045] - at least one digital processing server (11) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process the digital data measured through the sensor device (3); to run models such as machine learning techniques, full deep neural networks, decision trees, Gradient Boosting models and support vector machines (SVM), on this data;

[0046] - at least one natural language processing server (12) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process patient form, diagnosis form and treatment form textbased data on the user interface server (6); to analyze these texts by means of large language processing models; to extract meaning and to produce results; and thus to make sense of the patient’s story and the doctor’s comments;

[0047] - at least one time-sequenced relationship processing server (13) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process the data based on time-sequenced relationships; to process the network functions by running artificial neural network models on patient follow-up data and historical diagnosis-treatment data on the virtualization server (5); and to produce results;

[0048] - at least one training and improvement server (14) which is configured to establish connection with the artificial intelligence server (9) by using any communication protocol; to train, update and keep record of the artificial intelligence models by accessing the data on the artificial intelligence server (9); to ensure that specialized artificial intelligence models specific to each disease are trained and the models are stored and managed; to decide which model to use and how to train via artificial intelligence models developed specific to the disease; and to ensure better detection of the disease via artificial intelligence models developed specifically for the disease;

[0049] - at least one integration server (15) which is configured to manage the integrations necessary for collection, transmission, storage and processing of data; to assess the compliance of data transfers with legal and ethical compliance policies; and to make adjustments in order to integrate these policies;

[0050] - at least one legal and ethical compliance server (16) which is configured to conduct legal and ethical assessments and to perform integration according to these assessments; to monitor compliance with existing laws; to manage patient authorizations and fulfill legal provisions; and to ensure that patient information is used within an ethical and legal framework.

[0051] The visual measurement device (2) included in the inventive system (1) is configured to establish connection with the loT devices management server (4) by using any communication protocol included in the state of the art. The visual measurement device (2) is configured to generate imaging results such as MRI (Magnetic Resonance Imaging), X-ray, ultrasound. The vision measurement device (2) is configured to capture the medical data received from patients and to transmit it to the loT devices management server (4). The sensor device (3) included in the inventive system (1) is configured to establish connection with the loT devices management server (4) by using any communication protocol included in the state of the art. The sensor device (3) is configured to comprise measurement devices such as ECG (Electrocardiography) devices, blood test sensors, pulse measurement devices. The sensor device (3) is configured to capture the medical data received from patients and to transmit it to the loT devices management server (4).

[0052] The loT devices management server (4) included in the inventive system (1) is configured to establish connection with the visual measurement device (2) and the sensor device (3) and to access the data thereon by using any communication protocol included in the state of the art. The loT devices management server (4) is configured to transfer and manage the data in a coordinated way. The loT devices management server (4) is configured to transfer the collected data to other servers over the mobile network.

[0053] The network functions virtualization server (5) included in the inventive system (1) is configured establish connection with the loT devices management server (4) by using any communication protocol included in the state of the art. The network functions virtualization server (5) is configured to access the data transmitted by the loT devices management server (4) over the mobile network. The network functions virtualization server (5) is configured to ensure that the data transmitted by the loT devices management server (4) is transported to other servers through the core network which is responsible for managing virtual functions in 5G and beyond networks. The network functions virtualization server (5) is configured to be built on edge computing technology. The network functions virtualization server (5) is configured to ensure data processing, data transfer, data integration and data management by hosting specialized virtual functions. The network functions virtualization server (5) is configured to scale data processing together with virtualization technology of network functions and to run more functions according to need. The network functions virtualization server (5) is configured to provide fast, scalable, low-latency service with virtualization technology of network functions. The network functions virtualization server (5) is configured to use specialized virtual network functions in order to provide the data needed by artificial intelligence models quickly.

[0054] The user interface server (6) included in the inventive system (1) is configured to establish connection with the integration server (15) and the legal and ethical compliance server (16) by using any communication protocol included in the state of the art. The user interface server (6) is configured to establish connection with the patient electronic device (HE) and health worker electronic device (SE) by using any communication protocol included in the state of the art. The user interface server (6) is configured to enable patients to view, control and manage their data over the patient electronic device (HE). The user interface server (6) is configured to enable healthcare workers to view, update the patients’ information and to manage permissions and to track patients over the healthcare worker electronic device (SE). The user interface server (6) is configured to arrange and manage permits according to the data it accessess over the integration server (15) and the legal and ethical compliance server (16). The user interface server (6) is configured to produce and keep record of patient forms, diagnosis forms and treatment forms that are standardized therein and can be filled in by healthcare professionals and patients.

[0055] The data storage server (7) included in the inventive system (1) is configured to establish connection with the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by using any communication protocol included in the state of the art and to access and to keep record of these data. The data storage server (7) is configured to keep record of patient and healthcare worker information. The data storage server (7) is configured to transmit any data that needs to be transmitted to other servers, over the security server (8). The security server (8) included in the inventive system (1) is configured to establish connection with the data storage server (7) by using any communication protocol included in the state of the art. The security server (8) is configured to implement security measures in order to prevent patient information from falling into the hands of unintended persons.

[0056] The artificial intelligence server (9) included in the inventive system (1) is configured to access the data on the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by establishing connection with the security server (8) by using any communication protocol included in the state of the art. The artificial intelligence server (9) is configured to include specialized servers according to the type of data. The artificial intelligence server (9) is configured to establish connection with the visual processing server (10), the digital processing server (11), the natural language processing server (12) and the time-sequenced relationship processing server (13) by using any communication protocol included in the state of the art. The artificial intelligence server (9) is configured to establish connection with the training and improvement server (14) by using any communication protocol included in the state of the art. The artificial intelligence server (9) is configured to process and analyze the data in a systematic way. The artificial intelligence server (9) is configured to access all data processed on the visual processing server (10), the digital processing server (11), the natural language processing server (12) and the time-sequenced relationship processing server (13) and then to combine these data in a unifying layer; to form a single vector thereof; to process this vector containing the combined data in an output model by using deep neural networks; and to generate diagnosis and treatment recommendations by generating results.

[0057] The visual processing server (10) included in the inventive system (1) is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol included in the state of the art. The visual processing server (10) is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data. The visual processing server (10) is configured to process the images displayed through the visual measurement device (2); to run visual processing-based deep learning models in the form of convolutional neural networks (CNN) on these images; to analyze the images and to produce results.

[0058] The digital processing server (11) included in the inventive system (1) is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol included in the state of the art. The digital processing server (11) is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data. The digital processing server (11) is configured to process the digital data measured through the sensor device (3); to run models such as machine learning techniques, full deep neural networks (DNN), decision trees, Gradient Boosting models and support vector machines (SVM), on this data.

[0059] The natural language processing server (12) included in the inventive system (1) is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol included in the state of the art. The natural language processing server (12) is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data. The natural language processing server (12) is configured to process patient form, diagnosis form and treatment form text-based data on the user interface server (6); to analyze these texts by means of large language processing models (LLM); to extract meaning and to produce results; and thus to make sense of the patient’s story and the doctor’s comments.

[0060] The time-sequenced relationship processing server (13) included in the inventive system (1) is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol included in the state of the art. The time-sequenced relationship processing server (13) is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data. The time-sequenced relationship processing server (13) is configured to process the data based on time-sequenced relationships. The time-sequenced relationship processing server (13) is configured to process the network functions by running artificial neural network models (RNN) on patient follow-up data and historical diagnosis-treatment data on the virtualization server (5); and to produce results.

[0061] The training and improvement server (14) included in the inventive system (1) is configured to establish connection with the artificial intelligence server (9) by using any communication protocol included in the state of the art. The training and improvement server (14) is configured to train, update and keep record of the artificial intelligence models by accessing the data on the artificial intelligence server (9). The training and improvement server (14) is configured to ensure that specialized artificial intelligence models specific to each disease are trained and the models are stored and managed. The training and improvement server (14) is configured to decide which model to use and how to train via artificial intelligence models developed specific to the disease. The training and improvement server (14) is configured to ensure better detection of the disease via artificial intelligence models developed specifically for the disease.

[0062] The integration server (15) included in the inventive system (1) is configured to manage the integrations necessary for collection, transmission, storage and processing of data. The integration server (15) is configured to assess the compliance of data transfers with legal and ethical compliance policies; and to make adjustments in order to integrate these policies.

[0063] The legal and ethical compliance server (16) included in the inventive system (1) is configured to conduct legal and ethical assessments and to perform integration according to these assessments. The legal and ethical compliance server (16) is configured to monitor compliance with existing laws; to manage patient authorizations and fulfill legal provisions; and to ensure that patient information is used within an ethical and legal framework.

[0064] Industrial Application of the Invention

[0065] In the inventive system (1), the artificial intelligence server (9) accesses the data on the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by establishing connection with the security server (8) by using any communication protocol. The artificial intelligence server (9) includes specialized servers according to the type of data. The artificial intelligence server (9) establishes connection with the visual processing server (10), the digital processing server (11), the natural language processing server (12) and the time-sequenced relationship processing server (13) by using any communication protocol and comprises these servers. The artificial intelligence server (9) establishes connection with the training and improvement server (14) by using any communication protocol. The artificial intelligence server (9) processes and analyzes the data in a systematic way. The artificial intelligence server (9) accesses all data processed on the visual processing server (10), the digital processing server (11), the natural language processing server (12) and the time-sequenced relationship processing server (13) and then combines these data in a unifying layer; forms a single vector thereof; processes this vector containing the combined data in an output model by using deep neural networks; and generates a diagnosis and treatment recommendation by generating results. The visual processing server (10) establishes connection with the artificial intelligence server (9) and accesses the data thereon by using any communication protocol. The visual processing server (10) uses artificial intelligence models in order to better analyze and evaluate the hospital data. The visual processing server (10) processes the images displayed through the visual measurement device (2); runs visual processing-based deep learning models in the form of convolutional neural networks (CNN) on these images; analyzes the images and produces results. The digital processing server (11) establishes connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol. The digital processing server (11) uses artificial intelligence models in order to better analyze and evaluate the hospital data. The digital processing server (11) processes the digital data measured through the sensor device (3); run models such as machine learning techniques, full deep neural networks (DNN), decision trees, Gradient Boosting models and support vector machines (SVM), on this data. The natural language processing server (12) establishes connection with the artificial intelligence server (9) and accesses the data thereon by using any communication protocol. The natural language processing server (12) uses artificial intelligence models in order to better analyze and evaluate the hospital data. The natural language processing server (12) processes patient form, diagnosis form and treatment form text-based data on the user interface server (6); analyzes these texts by means of large language processing models (LLM); extracts meaning and produces results; and thus makes sense of the patient’s story and the doctor’s comments. The time-sequenced relationship processing server (13) establishes connection with the artificial intelligence server (9) and accesses the data thereon by using any communication protocol. The time-sequenced relationship processing server (13) uses artificial intelligence models in order to better analyze and evaluate the hospital data. The time-sequenced relationship processing server (13) processes the data based on time-sequenced relationships. The time-sequenced relationship processing server (13) processes the network functions by running artificial neural network models (RNN) on patient follow-up data and historical diagnosis-treatment data on the virtualization server (5); and produces results. The training and improvement server (14) establishes connection with the artificial intelligence server (9) by using any communication protocol. The training and improvement server (14) trains, updates and keeps record of the artificial intelligence models by accessing the data on the artificial intelligence server (9). The training and improvement server (14) ensures that specialized artificial intelligence models specific to each disease are trained and the models are stored and managed. The training and improvement server (14) decides which model to use and how to train via artificial intelligence models developed specific to the disease. The training and improvement server (14) ensures better detection of the disease via artificial intelligence models developed specifically for the disease. Thereby, it is ensured that tests, diagnoses and other examinations in hospitals are collected by means of standardized forms and these data are processed through 5G and beyond networks to make diagnosis via artificial intelligence.

[0066] Within these basic concepts; it is possible to develop various embodiments of the inventive “System (1) for Making a Diagnosis via Artificial Intelligence by Processing Hospital Data through 5G and Beyond Networks”; the invention cannot be limited to examples disclosed herein and it is essentially according to claims.

Claims

CLAIMS1. A system (1) which is developed for collecting tests, diagnoses and other examinations in hospitals by means of standardized forms and making a diagnosis via artificial intelligence by processing this data through 5G and beyond networks; characterized by- at least one visual measurement device (2) which is configured to produce imaging results and to capture the medical data received from patients;- at least one sensor device (3) which is configured to comprise measuring devices such as blood test sensors and pulse meters and to capture the medical data received from patients;- at least one loT devices management server (4) which is configured to establish connection with the visual measurement device (2) and the sensor device (3) and to access the data thereon by using any communication protocol; to ensure data transfer and management in a coordinated way; and to transfer the collected data to other servers over the mobile network;- at least one network functions virtualization server (5) which is configured establish connection with the loT devices management server (4) by using any communication protocol; to access the data transmitted by the loT devices management server (4) over the mobile network; to ensure that the data transmitted by the loT devices management server (4) is transported to other servers through the core network which is responsible for managing virtual functions in 5G and beyond networks; to be built on edge computing technology; to ensure data processing, data transfer, data integration and data management by hosting specialized virtual functions; to scale data processing together with virtualization technology of network functions and to run more functions according to need; to provide fast, scalable, low-latencyservice with virtualization technology of network functions; to use specialized virtual network functions in order to provide the data needed by artificial intelligence models quickly;- at least one user interface server (6) which is configured to establish connection with the patient electronic device (HE) and health worker electronic device (SE) by using any communication protocol; to access data; to enable patients to view, control and manage their data over the patient electronic device (HE); to enable healthcare workers to view, update the patients’ information, to manage permissions and to track patients over the healthcare worker electronic device (SE); to arrange and manage permits; to produce and keep record of patient forms, diagnosis forms and treatment forms that are standardized therein and can be filled in by healthcare professionals and patients;- at least one data storage server (7) which is configured to establish connection with the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by using any communication protocol; to access and to keep record of the data thereon; and to keep record of patient and healthcare worker information;- at least one security server (8) which is configured to establish connection with the data storage server (7) by using any communication protocol and to implement security measures in order to prevent patient information from falling into the hands of unintended persons;- at least one artificial intelligence server (9) which is configured to access the data on the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by establishing connection with the security server (8) by using any communication protocol; to include specialized servers according to the type of data; to process and analyze the data in asystematic way; to access all processed data and to combine it in a unifying layer; to form a single vector thereof; to process this vector containing the combined data in an output model by using deep neural networks; and to generate diagnosis and treatment recommendations by generating results;- at least one visual processing server (10) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process the images displayed through the visual measurement device (2); and to run visual processingbased deep learning models in the form of convolutional neural networks on these images; to analyze the images and to produce results;- at least one digital processing server (11) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process the digital data measured through the sensor device (3); to run models such as machine learning techniques, full deep neural networks, decision trees, Gradient Boosting models and support vector machines (SVM), on this data;- at least one natural language processing server (12) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process patient form, diagnosis form and treatment form text-based data on the user interface server (6); to analyze these texts by means of large language processing models; to extract meaning and toproduce results; and thus to make sense of the patient’s story and the doctor’s comments;- at least one time-sequenced relationship processing server (13) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol; to use artificial intelligence models in order to better analyze and evaluate the hospital data; to process the data based on time-sequenced relationships; to process the network functions by running artificial neural network models on patient follow-up data and historical diagnosis-treatment data on the virtualization server (5); and to produce results;- at least one training and improvement server (14) which is configured to establish connection with the artificial intelligence server (9) by using any communication protocol; to train, update and keep record of the artificial intelligence models by accessing the data on the artificial intelligence server (9); to ensure that specialized artificial intelligence models specific to each disease are trained and the models are stored and managed; to decide which model to use and how to train via artificial intelligence models developed specific to the disease; and to ensure better detection of the disease via artificial intelligence models developed specifically for the disease;- at least one integration server (15) which is configured to manage the integrations necessary for collection, transmission, storage and processing of data; to assess the compliance of data transfers with legal and ethical compliance policies; and to make adjustments in order to integrate these policies;- at least one legal and ethical compliance server (16) which is configured to conduct legal and ethical assessments and to perform integration according to these assessments; to monitor compliance with existing laws; to manage patient authorizations and fulfilllegal provisions; and to ensure that patient information is used within an ethical and legal framework.

2. A system (1) according to Claim 1; characterized by the visual measurement device (2) which is configured to establish connection with the loT devices management server (4) by using any communication protocol.

3. A system (1) according to Claim 1 or 2; characterized by the visual measurement device (2) which is configured to generate imaging results such as MRI, X-ray, ultrasound.

4. A system (1) according to Claim 3; characterized by the visual measurement device (2) which is configured to capture the medical data received from patients and to transmit it to the loT devices management server (4).

5. A system (1) according to any of the preceding claims; characterized by the sensor device (3) which is configured to establish connection with the loT devices management server (4) by using any communication protocol.

6. A system (1) according to any of the preceding claims; characterized by the sensor device (3) which is configured to comprise measurement devices such as ECG devices, blood test sensors, pulse measurement devices.

7. A system (1) according to any of the preceding claims; characterized by the sensor device (3) which is configured to capture the medical data received from patients and to transmit it to the loT devices management server (4).

8. A system (1) according to any of the preceding claims; characterized by the loT devices management server (4) which is configured to establish connection with the visual measurement device (2) and the sensor device (3) and to access the data thereon by using any communication protocol.

9. A system (1) according to any of the preceding claims; characterized by the loT devices management server (4) which is configured to transfer and manage the data in a coordinated way.

10. A system (1) according to any of the preceding claims; characterized by the loT devices management server (4) which is configured to transfer the collected data to other servers over the mobile network.

11. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured establish connection with the loT devices management server (4) by using any communication protocol.

12. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured to access the data transmitted by the loT devices management server (4) over the mobile network.

13. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured to ensure that the data transmitted by the loT devices management server (4) is transported to other servers through the core network which is responsible for managing virtual functions in 5G and beyond networks.

14. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured to be built on edge computing technology.

15. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured to ensure data processing, data transfer, data integration and data management by hosting specialized virtual functions.

16. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured to scale data processing together with virtualization technology of network functions and to run more functions according to need.

17. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured to provide fast, scalable, low-latency service with virtualization technology of network functions.

18. A system (1) according to any of the preceding claims; characterized by the network functions virtualization server (5) which is configured to use specialized virtual network functions in order to provide the data needed by artificial intelligence models quickly.

19. A system (1) according to any of the preceding claims; characterized by the user interface server (6) which is configured to establish connection with the integration server (15) and the legal and ethical compliance server (16) by using any communication protocol.

20. A system (1) according to any of the preceding claims; characterized by the user interface server (6) which is configured to establish connection with the patient electronic device (HE) and health worker electronic device (SE) by using any communication protocol.

21. A system (1) according to any of the preceding claims; characterized by the user interface server (6) which is configured to enable patients to view, control and manage their data over the patient electronic device (HE).

22. A system (1) according to any of the preceding claims; characterized by the user interface server (6) which is configured to enable healthcare workers to view, update the patients’ information and to manage permissions and to track patients over the healthcare worker electronic device (SE).

23. A system (1) according to any of the preceding claims; characterized by the user interface server (6) which is configured to arrange and manage permits according to the data it accessess over the integration server (15) and the legal and ethical compliance server (16).

24. A system (1) according to any of the preceding claims; characterized by the user interface server (6) which is configured to produce and keep record of patient forms, diagnosis forms and treatment forms that are standardized therein and can be filled in by healthcare professionals and patients.

25. A system (1) according to any of the preceding claims; characterized by the data storage server (7) which is configured to establish connection with the loT devices management server (4), the network functionsvirtualization server (5) and the user interface server (6) by using any communication protocol and to access and to keep record of these data.

26. A system (1) according to any of the preceding claims; characterized by the data storage server (7) which is configured to keep record of patient and healthcare worker information.

27. A system (1) according to any of the preceding claims; characterized by the data storage server (7) which is configured to transmit any data that needs to be transmitted to other servers, over the security server (8).

28. A system (1) according to any of the preceding claims; characterized by the security server (8) which is configured to establish connection with the data storage server (7) by using any communication protocol.

29. A system (1) according to any of the preceding claims; characterized by the security server (8) which is configured to implement security measures in order to prevent patient information from falling into the hands of unintended persons.

30. A system (1) according to any of the preceding claims; characterized by the artificial intelligence server (9) which is configured to access the data on the loT devices management server (4), the network functions virtualization server (5) and the user interface server (6) by establishing connection with the security server (8) by using any communication protocol.

31. A system (1) according to any of the preceding claims; characterized by the artificial intelligence server (9) which is configured to include specialized servers according to the type of data.

32. A system (1) according to any of the preceding claims; characterized by the artificial intelligence server (9) which is configured to establish connection with the visual processing server (10), the digital processing server (11), the natural language processing server (12) and the time- sequenced relationship processing server (13) by using any communication protocol.

33. A system (1) according to any of the preceding claims; characterized by the artificial intelligence server (9) which is configured to establish connection with the training and improvement server (14) by using any communication protocol.

34. A system (1) according to any of the preceding claims; characterized by the artificial intelligence server (9) which is configured to process and analyze the data in a systematic way.

35. A system (1) according to any of the preceding claims; characterized by the artificial intelligence server (9) which is configured to access all data processed on the visual processing server (10), the digital processing server (11), the natural language processing server (12) and the time- sequenced relationship processing server (13) and then to combine these data in a unifying layer; to form a single vector thereof; to process this vector containing the combined data in an output model by using deep neural networks; and to generate diagnosis and treatment recommendations by generating results.

36. A system (1) according to any of the preceding claims; characterized by the visual processing server (10) which is configured to establishconnection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol.

37. A system (1) according to any of the preceding claims; characterized by the visual processing server (10) which is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data.

38. A system (1) according to any of the preceding claims; characterized by the visual processing server (10) which is configured to process the images displayed through the visual measurement device (2); to run visual processing-based deep learning models in the form of convolutional neural networks on these images; to analyze the images and to produce results.

39. A system (1) according to any of the preceding claims; characterized by the digital processing server (11) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol.

40. A system (1) according to any of the preceding claims; characterized by the digital processing server (11) which is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data.

41. A system (1) according to any of the preceding claims; characterized by the digital processing server (11) which is configured to process the digital data measured through the sensor device (3); to run models such as machine learning techniques, full deep neural networks, decision trees, Gradient Boosting models and support vector machines, on this data.

42. A system (1) according to any of the preceding claims; characterized by the natural language processing server (12) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol.

43. A system (1) according to any of the preceding claims; characterized by the natural language processing server (12) which is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data.

44. A system (1) according to any of the preceding claims; characterized by the natural language processing server (12) which is configured to process patient form, diagnosis form and treatment form text-based data on the user interface server (6); to analyze these texts by means of large language processing models (LLM); to extract meaning and to produce results; and thus to make sense of the patient’s story and the doctor’s comments.

45. A system (1) according to any of the preceding claims; characterized by the time-sequenced relationship processing server (13) which is configured to establish connection with the artificial intelligence server (9) and to access the data thereon by using any communication protocol.

46. A system (1) according to any of the preceding claims; characterized by the time-sequenced relationship processing server (13) which is configured to use artificial intelligence models in order to better analyze and evaluate the hospital data.

47. A system (1) according to any of the preceding claims; characterized by the time-sequenced relationship processing server (13) which is configured to process the data based on time-sequenced relationships.

48. A system (1) according to any of the preceding claims; characterized by the time-sequenced relationship processing server (13) which is configured to process the network functions by running artificial neural network models on patient follow-up data and historical diagnosis-treatment data on the virtualization server (5); and to produce results.

49. A system (1) according to any of the preceding claims; characterized by the training and improvement server (14) which is configured to establish connection with the artificial intelligence server (9) by using any communication protocol.

50. A system (1) according to any of the preceding claims; characterized by the training and improvement server (14) which is configured to train, update and keep record of the artificial intelligence models by accessing the data on the artificial intelligence server (9).

51. A system (1) according to any of the preceding claims; characterized by the training and improvement server (14) which is configured to ensure that specialized artificial intelligence models specific to each disease are trained and the models are stored and managed.

52. A system (1) according to any of the preceding claims; characterized by the training and improvement server (14) which is configured to decide which model to use and how to train via artificial intelligence models developed specific to the disease.

53. A system (1) according to any of the preceding claims; characterized by the training and improvement server (14) which is configured to ensurebetter detection of the disease via artificial intelligence models developed specifically for the disease.

54. A system (1) according to any of the preceding claims; characterized by the integration server (15) which is configured to manage the integrations necessary for collection, transmission, storage and processing of data.

55. A system (1) according to any of the preceding claims; characterized by the integration server (15) which is configured to assess the compliance of data transfers with legal and ethical compliance policies; and to make adjustments in order to integrate these policies.

56. A system (1) according to any of the preceding claims; characterized by the legal and ethical compliance server (16) which is configured to conduct legal and ethical assessments and to perform integration according to these assessments.

57. A system (1) according to any of the preceding claims; characterized by the legal and ethical compliance server (16) which is configured to monitor compliance with existing laws; to manage patient authorizations and fulfill legal provisions; and to ensure that patient information is used within an ethical and legal framework.

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