6 results about "Squamous cancer" patented technology

The present application provides the use of liposome mitoxantrone hydrochloride in the preparation of a medicament for treating ovarian cancer, gastric cancer or head and neck squamous cancer, a method for treating ovarian cancer, gastric cancer or head and neck squamous cancer by using liposome mitoxantrone hydrochloride preparation, and a liposome mitoxantrone hydrochloride preparation for treating ovarian cancer, gastric cancer or head and neck squamous cancer.

Applicant provides herein methods for treating a patient having a pre-cancerous oral leukoplakia (LK) lesion or for delaying the progression of a pre-cancerous oral LK to oral squamous cell carcinoma. It also provides methods to identify patients that more likely to respond to a therapy comprising administration of an effective amount of an anti-PD-1 or anti-PD-L 1 therapy.

The present application belongs to the technical field of slice image recognition, and particularly relates to a cervical cell pathological slice recognition method based on multi-modal learning, which comprises the following steps: acquiring cervical pathological slice images and clinical text data of a patient, extracting image modal feature vectors and text modal feature vectors through an image encoder and a text encoder respectively; inputting the two modal features into a cross-modal fusion network constructed based on an asymmetric attention mechanism, guiding image feature enhancement with the text feature as a query, guiding text feature enhancement with the image feature as a query, and fusing to generate multi-modal joint feature representation; and outputting classification results such as normal cells, low-grade lesions, high-grade lesions or squamous cell carcinoma based on the joint feature representation. Through bidirectional cross-modal attention interaction, the present application realizes effective fusion of pathological image morphological features and clinical text information, and makes up for the limitations of single-modal data.

Systems and methods are provided for determining a cancer type of a somatic tissue in a subject. A first plurality of sequence reads is obtained from a plurality of RNA molecules in a biopsy of the subject. A first set of sequence features comprising relative mRNA abundance values of genes is determined from the first plurality of sequence reads. Sequence features are applied to a classification model trained to distinguish between each cancer type in a set of at least 50 cancer types, thus determining the cancer type of the somatic tissue in the subject. The classification model provides an indication that the somatic tissue is or is not a respective cancer type, and the set of cancer types includes at least two cancer types from one or more classes of cancer selected from the group consisting of hematological cancers, squamous cancers, endometrial cancers, sarcoma cancers, and neuroendocrine cancers.

The present disclosure relates to the treatment of solid cancers, such as breast cancer, colon cancer, and lung cancer (particularly non-small cell lung cancer (NSCLC)), in human subjects using anti-PD-1 antibodies as monotherapy or as combination therapy with, for example, chemotherapy and / or surgery. The treatments provided may be a combination of tiralizumab and chemotherapy prior to surgery, using different doses of tiralizumab in an auxiliary stage after surgery. Administration regimens may include administration of 200 mg of an anti-PD-1 antibody (e.g., tiralizumab) (e.g., every three weeks) followed by tumor resection, followed by administration of 400 mg of the anti-PD-1 antibody (e.g., every six weeks). Furthermore, the chemotherapy may be platinum-based (e.g., carboplatin and / or cis-platinum), and may further include pemetrexed (e.g., for non-squamous cancer) or paclitaxel (e.g., for squamous cancer).

The application belongs to the field of intelligent medical treatment, and particularly relates to a prediction method, device and medium for the absolute risk of esophageal squamous cell carcinoma. The method comprises the following steps: obtaining the hard food preference score, high-temperature food preference score and other clinical characteristics of a to-be-tested person, wherein the other clinical characteristics comprise age; calculating an unhealthy eating habit score based on the hard food preference score and the high-temperature food preference score; inputting the unhealthy eating habit score and the other clinical characteristics into an esophageal squamous cell carcinoma absolute risk prediction model to obtain the absolute risk of the to-be-tested person suffering from esophageal squamous cell carcinoma. The application calculates an unhealthy eating habit score based on the hard food preference score and the high-temperature food preference score, and determines that the unhealthy eating habit score is an effective predictor of the absolute risk of esophageal squamous cell carcinoma.