Diagnose known diseases from scans, images, biopsies, audio and other data

Imperial College Researchers diagnose ovarian cancer patients with survival rates under 2 years

Researchers at Osaka University differentiate between different types of cancer cells using a convolutional neural network

NYU researchers detected lymphedema with 93.8% accuracy using neural networks

Infervision successfully annotates lung nodules in scans using machine learning

Novartis researchers train algorithm to identify different cell types to spot cancer in scans

Enlicit classifies malignant tumours with 50% better accuracy than humans and 0 false-negatives with deep learning

Beijing Tian Tan Hospital is testing the detection of type, location and severity of a stroke using machine learning

University of Toronto aims to early detect individuals at risk for clinical decline with the use of machine learning

Mayo Clinic researchers accurately diagnose hyperkalemia using a smartphone electrocardiogram device

Researchers aim to identify fibromyalgia patients from fMRI images using machine learning

Researchers at University of Washington explore diagnosis of early onset of pancreatic cancer by identifying increased bilirubin levels in sclera from selfies with 89% accuracy

Google Research detects diabetic eye disease as well as leading ophthalmologists with machine learning

DeepMind aims to improve machine learning system to detect breast cancer from images with more diverse dataset

UCLH plans to use machine learning to triage patients in A&E and better predict demand for the service

Capitol Health improves accuracy of diagnosis from scans, X-rays etc using deep learning

PlantVillage detects multiple diseases in Cassava plants with machine learning

Aravind Eye Hospital identifies eye complications arising from diabetes with a 97.5% accuracy using machine learning

Danish emergency service dispatchers identify heart-attacks in real-time emergency calls with 95% accuracy, compared to 73% for human dispatchers, with real-time speech analysis and machine learning

Researchers propose a new method for automating the contouring of high-risk clinical target volumes using neural networks

University of Southern California researchers determine an efficient combination of tests to accurately predict FASD in children

University of Nottingham uses machine learning to beat doctors at predicting who will have heart attacks over the next ten years that could result in an additional 355 additional lives being saved

Enlitic augments radiologists to achieve 21% faster, 11% more sensitive and 9% more specific reading of fractures in X-rays with deep learning

Researchers at UCLA develop a convolutional neural networks system that detects prostate cancer as well as experienced radiologists in detecting prostate cancer

Imagen Tech''s Osteodetect platform which uses deep learning to detect wrist fractures has acquired FDA approval

New York University and IBM Research to assess the presence of glaucoma in the retina using deep learning

SocialEyes diagnoses diseases in places where doctors are scarce by scanning the human retina with deep neural networks at the edge

Scientists automate detection of polyps during colonoscopy using deep learning

Niramai develops screening tool that improves breast cancer diagnosis using machine learning

DeepMind achieves human specialist accuracy in diagnosing retina disease based on scans using machine learning

Unanimous AI achieves 22% more accurate pneumonia diagnoses with the use of "swarm intelligence"

Researchers at Stanford University identify depression in patients with 80% accuracy using machine learning

Anglia Ruskin University researchers develop mobile system which detects tuberculosis with 98.4% accuracy

Oregon Health and Science University trained deep learning models on used machine learning to diagnose the leading childhood blindness disease with 91% accuracy bettering the 82% of opthalmologists

Stanford University Medical uses deep convolutional neural networks to predict skin cancer as well as dermatologists

Qure.ai achieves 90% accuracy using deep learning to diagnose pulmonary consolidation in chest x-rays

National University of Singapore researchers use deep learning to outperform current methods in detecting glaucoma progression in patients

Clinicial researchers at Imperial College London and the University of Edinburgh develop machine learning based software that could speed up treatment of patients showing signs of stroke or dementia

Stanford University trained deep neural networks to predict skin carcinomas from images with the same accuracy as determatologists

Viz.ai''s deep learning solution which automatically detects strokes from CTA scans reducing detection time from 66 to 6 minutes has earned FDA approval

MIT researchers propose an efficient and accurate system for protecting privacy in healthcare datasets

Stanford University Parker Institute for Cancer Immunotherapy predict childhood leukemia patients relapse with 85% accuracy using machine learning

The University of Alberta and IBM can predict schizophrenia with 74% accuracy by looking at images of the brain''s blood flow

London Hospital for Tropical Diseases is testing an AI powered microscope which detects the presence of malaria parasites in blood with the same accuracy as microscopists

Qure.ai can detect critical head trauma or stroke symptoms from CT scans with more than 95% accuracy using deep neural networks and natural language processing

Researchers at Macau University of Science and Technology develop a new model for disease classification in cases of limited labelled data with ~90% accuracy by combining logistic regression and semi-supervised learning

IDX launched the first FDA approved artificial intelligence service that can diagnose the eye disease diabetic retinopathy without a clinician''s involvement

Baidu builds automated cat shelter for strays using image recognition

Japan to automate patient information entry and some medical procedures by investing in 10 AI-powered hospitals

Szechwan People’s Hospital uses machine learning to detect early signs of lung cancer in CT scans broadening access to quality diagnosis given the scarcity of radiologists in China

Researchers in South Korea demonstrate accuracy of 98.8% in diagnosing Parkinson''s disease using convoluted neural networks

Google''s Verily prioritizes patients by diagnosing retinopathy more accurately than ophthalmologists using deep neural networks