390 results about "Diabetes retinopathy" patented technology

The invention relates to new therapeutically active and selective inhibitors of the enzyme dipeptidyl peptidase-IV, pharmaceutical compositions comprising the compounds and the use of such compounds for treating diseases that are associated with proteins that are subject to processing by DPP-IV, such as Type 2 diabetes mellitus, hyperglycemia, impaired glucose tolerance, metabolic syndrome (Syndrome X or insulin resistance syndrome), glucosuria, metabolic acidosis, cataracts, diabetic neuropathy, diabetic nephropathy, diabetic retinopathy, diabetic cardiomyopathy, Type 1 diabetes, obesity, conditions exacerbated by obesity, hypertension, hyperlipidemia, atherosclerosis, osteoporosis, osteopenia, frailty, bone loss, bone fracture, acute coronary syndrome, infertility due to polycystic ovary syndrome, short bowel syndrome, anxiety, depression, insomnia, chronic fatigue, epilepsy, eating disorders, chronic pain, alcohol addiction, diseases associated with intestinal motility, ulcers, irritable bowel syndrome, inflammatory bowel syndrome and to prevent disease progression in Type 2 diabetes. The invention also relates to a method of identifying an insulin secretagogue agent for diabetes.

The invention provides a method of optical imaging comprising providing a sample to be imaged, measuring and correcting aberrations associated with the sample using adaptive optics, and imaging the sample by optical coherence tomography. The method can be used to image the fundus of a human eye to provide diagnostic information about retinal pathologies such as macular degeneration, retinitis pigmentosa, glaucoma, or diabetic retinopathy. The invention further provides an apparatus comprising an adaptive optics subsystem and a two-dimensional optical coherence tomography subsystem.

This invention provides use of a SARM compound or a composition comprising the same in treating a variety of diseases or conditions in a subject, including, inter-alia, a diabetes disease, and/or disorder such as cardiovascular disease, atherosclerosis, cerebrovascular conditions, diabetic nephropathy, diabetic neuropathy and diabetic retinopathy.

The invention discloses an eye fundus image characteristics extraction method for diabetic retinopathy by utilizing an eye fundus image shot by a digital mydriatic-free eye fundus camera. The method comprises the following steps of (1) selecting an RGB channel of the eye fundus image; (2) positioning the optic disk of the eye fundus image; (3) extracting the hard exudate characteristics and the cotton wool spot characteristics of the eye fundus image, generating an extracted eye fundus image if at least one characteristic is discovered, if no characteristic is discovered, extracting microaneurysm characteristics and retinal hemorrhage characteristics, and generating an extracted eye fundus image. The method belongs to a non-intrusive technology, and is simple, rapid, convenient and effective, and the processed image is clear and obvious in symptom, so the diagnosis of a doctor is facilitated.

The present invention provides a fundus image classification method and device of retinopathy. The method comprises a step of obtaining the fundus image of an eye detection patient, a step of preprocessing the fundus image and obtaining a corresponding grey fundus image, a step of extracting a preset image characteristic in the grey fundus image, a step of analyzing the preset image characteristic according to the diabetic retinopathy classification model of the fundus image, and obtaining the classification result of the corresponding fundus image, a step of extracting the preset image characteristic in the preprocessed grey fundus image, and carrying out prediction classification on the above preset image characteristic through the diabetic retinopathy classification model established according to a support vector machine and a deep neural network so as to obtain a final classification result. The artificial participation is not needed in the whole process, the workload of doctors is reduced, the high standard requirement of the medical qualification level of the doctor is reduced, the accuracy of classification is improved, and the method and the device have great significance for specific applications and medical research.

The present invention relates to a method of making novel dipeptidyl peptidase-IV ("DPP-IV') inhibitor compounds useful for treating, inter alia, diseases that are associated with proteins that are subject to processing by DPP-IV, such as Type 2 diabetes mellitus, metabolic syndrome (Syndrome X or insulin resistance syndrome), hyperglycemia, impaired glucose tolerance, glucosuria, metabolic acidosis, cataracts, diabetic neuropathy, diabetic nephropathy, diabetic retinopathy, diabetic cardiomyopathy, Type 1 diabetes, obesity, hypertension, hyperlipidemia, atherosclerosis, osteoporosis, osteopenia, frailty, bone loss, bone fracture, acute coronary syndrome, infertility due to polycystic ovary syndrome, short bowel syndrome and to prevent disease progression in Type 2 diabetes. The invention also relates to a method of making 3,3,4,4-tetrafluoropyrrolidine, a starting material utilized in the afore-mentioned method for preparing DPP-IV compounds.

A method and kit for predicting increased risk of sight-threatening diabetic retinopathy which includes isolating genomic DNA from a sample from a diabetic patient. The genetic polymorphism pattern for the genes IL-1A, IL-1B and IL-1RN is then identified in the DNA. The identified pattern is compared with control patterns of known polymorphisms, and patients expressing a genetic polymorphism pattern associated with increased risk of sight-threatening diabetic retinopathy are identified.

A system for the imaging, processing and evaluation of tissues provides prognostic and diagnostic details regarding diseased tissue. A set of quantitative measures were developed and integrated in an image-base analysis software tool designed for OCT images. The system and methods in this invention is significant because it allows assessing the optical properties and structure morphology differences between normal healthy subjects and diabetic patients with retinopathy up to ETDRS level 35 and without retinopathy.

This invention provides reagents and methods for delivering insulin, insulinomimetic agents, and the like to a vertebrate eye via subconjunctival routes, sub-Tenon's routes, or intravitreal routes for treatment of nerve-related vision disorders such as diabetic retinopathy, and formulations useful in the practice of the disclosed methods.

This invention provides a method for treating diabetic retinopathy in a subject afflicted therewith, comprising administering to the subject's eyes a therapeutically effective amount of soluble RAGE or a derivative thereof, thereby treating diabetic retinopathy in the subject. This invention further provides a method for inhibiting the onset of diabetic retinopathy in a subject afflicted therewith, comprising administering a prophylactically effective amount of soluble RAGE or a derivative thereof to the subject's eyes, thereby inhibiting the onset of diabetic retinopathy in the subject.

The invention relates to a deep-learning-based classification and grading method for diabetes retinopathy. For each kind of diabetes retinopathy, lots of ophthalmoscope photographs are prepared; a deep convolution neural network including multi-level neural network architecture is established; the deep convolution neural network is trained based on the lots of ophthalmoscope photographs, so that the final output value of the deep convolution neural network meets a grading result of the ophthalmoscope photographs; and thus disease grading can be carried out by using the trained deep convolution neural network. According to the method provided by the invention, with application of the lots of ophthalmoscope photographs including diagnosis marks, needed features are learned automatically from a training example base by deep learning and grading diagnosis is carried out; and data features for determination and the deep convolution neural network parameters are corrected continuously during the training process, so that the grading accuracy and reliability in a real application scene can be improved substantially.

A fundus camera using infrared light sources, which included an imaging optical path and an optical path for focusing and positioning and two optical paths share a common set of retina objective lens, and a computer-assisted method for retinal vessel segmentation in general and diabetic retinopathy (DR) image segmentation in particular. The method is primarily based on Multiscale Production of the Matched Filter (MPMF) scheme, which together the fundus camera, is useful for non-invasive diabetic retinopathy detection and monitoring.

The invention provides a diabetic retinopathy fundus photography standard image generation method, which comprises the following steps: 1) enabling a collected non-standard fundus image to be generated into a new sample image through a generation model; 2) carrying out local feature extraction on the new sample image; and 3) comparing local features of the non-standard image with local features of a standard image in a discrimination model, if the local features are consistent, outputting the new sample image, that is, the generated standard image, and if the local features are not consistent, adjusting the new sample image. The provided method is simple and effective; the definition of the generated standard image reaches requirement of an intelligent aided diagnosis system; and accuracy of diagnosis is improved.

The invention discloses a diabetic retina eye ground image pathology detection method comprising the following steps: preprocessing a medical eye ground image so as to form a standard eye ground image; dividing areas for the eye ground image so as to form m sub-images of different eye ground areas; using a multilayer area convolution nerve network model to extract an area depth feature vector of the eye ground sub-image; using the area depth feature vector as the LSTM nerve network input, predicting correlations of different areas, and forming an eye ground image global feature vector; finally, using a whole articulamentum and softmax to realize multi-classification detection of the eye ground image. The method is based on retina eye ground images and labels that can be crawled on the internet, uses the correlation between the eye ground image area depth features and the adjacent area, and realizes the diabetic retina eye ground image pathology automatic detection via the convolution nerve network and recursion nerve network algorithms, thus effectively improving the detection accuracy and timeliness.

Chemical syntheses and medical uses of novel inhibitors of the uptake of monoamine neurotransmitters and pharmaceutically acceptable salts and prodrugs thereof, for the treatment and/or management of psychotropic disorders, anxiety disorder, generalized anxiety disorder, depression, post-traumatic stress disorder, obsessive-compulsive disorder, panic disorder, hot flashes, senile dementia, migraine, hepatopulmonary syndrome, chronic pain, nociceptive pain, neuropathic pain, painful diabetic retinopathy, bipolar depression, obstructive sleep apnea, psychiatric disorders, premenstrual dysphoric disorder, social phobia, social anxiety disorder, urinary incontinence, anorexia, bulimia nervosa, obesity, ischemia, head injury, calcium overload in brain cells, drug dependence, and/or premature ejaculation are described.

The invention provides a diabetic retinopathy grade classification method based on deep learning. The diabetic retinopathy grade classification method comprises the steps of: constructing a sample library; removing backgrounds and noise of ophthalmoscope photographs in the sample library; normalizing the images of different brightness and different intensity to the same range by adopting a local mean value subtracting method; adopting random stretching and rotating methods for different samples for data augmentation, and constructing a training set and a test set; training an initial deep learning network model by establishing an input portion architecture, a multi-branch feature transformation portion architecture and an output portion architecture separately; and inputting samples to betested into the trained initial deep learning network model for diabetic retinopathy grade classification. Compared with the traditional processing method, the diabetic retinopathy grade classification method gets rid of the dependence on prior knowledge, and has good generalization ability; and by adopting the designed multiple grades, a small-sized convolution kernel can be used for extracting very tiny lesion features, thereby making the classification results more reliable.

A non-surgical method for preventing or reducing the rate of the progression of non-proliferative diabetic retinopathy to the proliferative form of diabetic retinopathy comprising intravitreally administering to a patient suffering from non-proliferative diabetic retinopathy an effective amount of serine proteinase enzyme sufficient to create, without surgery, a posterior vitreal detachment to prevent or reduce the progression of proliferative diabetic retinopathy in said patient. Also disclosed is a non-surgical method of treating ocular conditions such as retinal ischemia, retinal inflammation, retinal edema tractional retinal detachment, tractional retinopathy, vitreous hemorrhage and tractional maculopathy by intravitreally administering to a patient suffering from one or more of these conditions with an effective amount of a serine proteinase enzyme to reduce or treat that particular ocular condition. Plasmin, microplasmin and miniplasmin are preferred serine proteinase enzymes and plasmin is the most preferred.

RNA interference, is provided for inhibition of HIF1A mRNA expression for treating patients with ocular angiogenesis, particularly for treating retinal edema, diabetic retinopathy, sequela associated with retinal ischemia, posterior segment neovascularization (PSNV), and neovascular glaucoma, and for treating patients at risk of developing such conditions.

The present invention relates to amide derivatives of Formula (XIIIa) and pharmaceutical compositions thereof that modulate the activity of the PGI2 receptor. Compounds of the present invention and pharmaceutical compositions thereof are directed to methods useful in the treatment of: pulmonary arterial hypertension (PAH); idiopathic PAH; familial PAH; PAH associated with a collagen vascular disease, a congenital heart disease, portal hypertension, HIV infection, ingestion of a drug or toxin, hereditary hemorrhagic telangiectasia, splenectomy, pulmonary veno-occlusive disease (PVOD) or pulmonary capillary hemangiomatosis (PCH); PAH with significant venous or capillary involvement; platelet aggregation; coronary artery disease; myocardial infarction; transient ischemic attack; angina; stroke; ischemia-reperfusion injury; restenosis; atrial fibrillation; blood clot formation in an angioplasty or coronary bypass surgery individual or in an individual suffering from atrial fibrillation; atherosclerosis; atherothrombosis; asthma or a symptom thereof; a diabetic-related disorder such as diabetic peripheral neuropathy, diabetic nephropathy or diabetic retinopathy; glaucoma or other disease of the eye with abnormal intraocular pressure; hypertension; inflammation; psoriasis; psoriatic arthritis; rheumatoid arthritis; Crohn's disease; transplant rejection; multiple sclerosis; systemic lupus erythematosus (SLE); ulcerative colitis; ischemia-reperfusion injury; restenosis; atherosclerosis; acne; type 1 diabetes; type 2 diabetes; sepsis; and chronic obstructive pulmonary disorder (COPD).