{"id":23035290,"url":"https://github.com/gdapriana/diadetect","last_synced_at":"2025-08-14T17:30:59.095Z","repository":{"id":199928027,"uuid":"704099847","full_name":"gdapriana/diadetect","owner":"gdapriana","description":"Machine learning program, to detect diabetes using classification algorithm, Neural Network","archived":false,"fork":false,"pushed_at":"2024-01-13T06:10:33.000Z","size":4826,"stargazers_count":4,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-07-29T21:22:05.605Z","etag":null,"topics":["nextjs","tensorflow"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/gdapriana.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-10-12T14:33:47.000Z","updated_at":"2024-07-29T21:22:05.606Z","dependencies_parsed_at":"2023-12-07T12:44:35.024Z","dependency_job_id":"f512b190-7224-47ee-a36e-642d98678696","html_url":"https://github.com/gdapriana/diadetect","commit_stats":null,"previous_names":["icequeenwand/diabetic-detection","gdapriana/diabetic-detection"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gdapriana%2Fdiadetect","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gdapriana%2Fdiadetect/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gdapriana%2Fdiadetect/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gdapriana%2Fdiadetect/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gdapriana","download_url":"https://codeload.github.com/gdapriana/diadetect/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":229846674,"owners_count":18133493,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["nextjs","tensorflow"],"created_at":"2024-12-15T16:39:52.898Z","updated_at":"2024-12-15T16:39:53.500Z","avatar_url":"https://github.com/gdapriana.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Diadetect\n\n\u003e ❗ still development\n\n![diadetect](https://github.com/gdapriana/diadetect/assets/69134731/097dc064-fa80-4d35-ac03-5cc0c306f5d0)\n\n\u003e Diadetect is an application designed to detect the likelihood of diabetes based on user-input data. The application utilizes a TensorFlow neural network for its predictive model and is built for mobile platforms using React Native.\n\n## ✅ Features\n\n- **User-Friendly Interface:** Intuitive and easy-to-use design for seamless user interaction.\n- **Predictive Model:** Powered by a TensorFlow neural network, DiaDetect provides accurate predictions based on input parameters.\n\n**Input Parameters:**\n\n| 📛 Name | ❓ How to get    | 📖 Description                |\n| :-------- | :------- | :------------------------- |\n| `Pregnancies` | This information is typically gathered from medical records or the patient's medical history. Patients can provide details about their previous pregnancies during medical consultations. | The number of pregnancies a woman has experienced. |\n| `Glucose levels` | Glucose levels are measured through blood tests. Patients can undergo blood tests at healthcare laboratories or use home blood glucose meters for self-monitoring. | The concentration of glucose (sugar) in the blood. |\n| `Blood pressure` | Blood pressure measurement is commonly done using a sphygmomanometer. This test can be performed at healthcare facilities, clinics, or even at home using digital blood pressure monitors. | The force of blood against the walls of the arteries, usually measured in millimeters of mercury (mmHg). |\n| `Skin thickness` | Measurement of skinfold thickness is typically done by healthcare professionals using a tool called a skinfold caliper. | Refers to the thickness of a fold of skin at a specific location on the body. |\n| `Insulin levels` | Insulin levels are measured through blood tests conducted in healthcare laboratories. | The amount of insulin in the blood, a hormone crucial for regulating blood sugar. |\n| `BMI (Body Mass Index)` | BMI is calculated based on weight and height measurements. Weight can be measured using scales, and height can be measured using a stadiometer. | A numerical value of a person's weight in relation to their height. |\n| `Diabetes pedigree function` | Information about the family history of diabetes is obtained from the patient. Patients provide details about whether any family members have a history of diabetes. | A function presenting the family history of diabetes and estimating the genetic risk associated with diabetes. |\n| `Age` | Age information is obtained directly from the patient during medical consultations or can be derived from personal identification data. | The age of the individual. |\n\n## Getting Started\n\n### Prerequisites\n\n- Node.js and npm installed\n- Python\n\n### Installation\n\n\u003e coming soon\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgdapriana%2Fdiadetect","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgdapriana%2Fdiadetect","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgdapriana%2Fdiadetect/lists"}