A Machine learning solution for Migraine Classification using Orange Tool

Diving into the challenges of data quality in women's healthcare, exploring real-life stories that highlight the critical need for accurate data collection and its impact on diagnoses, treatment, and pharmaceutical advancements. Shedding light on the persistent issues of gender bias in healthcare and advocating for the importance of quality data.

Record, track, and visualize your personal health data.

Config files for my GitHub profile.

This is a FHIR v4.0 TypeScript class library implementing the JSON schema that is built for those who want to source the data, like from a UI, and send that data to a data store.

Health insurance customer segmentation using KMean clustering approach

Created to graphically inform health professionals about metrics of the virus they may be interested in. This dashboard allows the user to view the number of deaths, recoveries and vaccinations that have occurred. The analysis was done in MS Excel while the visualization was worked on in Power BI.

A curated dataset of Indian medicines, organized by brand. Essential for healthcare research and pharmaceutical analysis.

A deep-learning model that can accurately predict hospital readmission rates for patients with specific medical conditions

this Is my HealthCare Website under Hack-a-thon HackFest( Delhi/NCR) GEEKS FOR Geeks which is still in working .The system should continuously gather and analyze healthcare data while promoting healthy lifestyles and wellness practices.

FHIR layer for healthcare data platform GameBus and beyond

A topic-centric list of HQ open datasets of Pakistan

Physician Office Visit Cost Data 📦

Convert DICOM files from DXA scans to other image formats, and parse the corresponding metadata files

Life saving notification script for doctors in US which notifies them when patient visits hospital via sms can be hosted on Cpanel

Class projects

Detección de cardiopatías en pacientes mediante el uso de datos clínicos utilizando técnicas de Machine Learning y Deep Learning.

Employed cutting-edge Machine Learning and Deep Learning algorithms, including SVM, Random Forest, and Neural Networks, to develop a dynamic framework for assessing pilots' qualification using Python and prominent ML libraries such as scikit-learn, TensorFlow, and PyTorch.

Implemented classification models on heart failure dataset to assess the likelihood of an event that can be attributed to cardiovascular disease with R