health-care-application

There are 9 repositories under health-care-application topic.

  • Kalpesh209/flutter_doctor_appointment_booking_app

    On Demand Doctor Appointment Booking App Built in Flutter

    Language:Dart603218
  • bentoml/Pneumonia-Detection-Demo

    Pneumonia Detection - Healthcare Imaging Application built with BentoML and fine-tuned Vision Transformer (ViT) model

    Language:Python8612
  • ASK-03/Cloudphysician

    A project aimed to address challenges in ICU care by leveraging machine learning and computer vision. The primary goal is to develop a system capable of extracting vital signs information from patient monitor images obtained through CCTV footage or dedicated cameras

    Language:Python5203
  • bzamith/ID_Agile-HH

    School of AI - Health Hackathon 30 and 31 March 2019

    Language:Python5100
  • abhiiiman/DocBuddy.ai

    DocBuddy.ai 🩺 Your Personalized 🪄 Doctor Buddy 👨🏻‍⚕️

    Language:Python2200
  • dsai-iitbhilai/Cloudphysician

    A project aimed to address challenges in ICU care by leveraging machine learning and computer vision. The primary goal is to develop a system capable of extracting vital signs information from patient monitor images obtained through CCTV footage or dedicated cameras

    Language:Python1000
  • ArpitSachan/dedatom-A-digital-health-care-system

    This repository contains a health care app based on geolocation and digitization of the health system. It includes real-time chat (to be encrypted) enabled with image-picker and hostpital finder using google maps api.

    Language:Dart0100
  • onkar69483/Scobo-Medical-Robot

    Scobo is an advanced robot designed to revolutionize the healthcare industry. Developed by the Rotonity Club, Scobo aims to ease doctors' workloads and enhance patient care through cutting-edge technology. It features a sophisticated Pill Dispensing System that streamlines medication management.

    Language:C++0100
  • Roshni-Bala/Breast-Cancer-Risk-Prediction

    Socially Relevant Project (SRP). Using the UCI breast cancer dataset to analyze and build a model with high accuracy, precision and recall. This could be used to predict whether a patient has a malignant or benign tumor based on the 10 different FNA cell parameters.

    Language:Jupyter Notebook10