AI Use Case

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

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



Risk reduction - Predictive diagnosis,Risk reduction - Patient outcomes,Operational - Process speed up,Cost - Staff efficiency

Case Studies

Szechwan People’s Hospital~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,"Beijing Tian Tan Hospital~Beijing Tian Tan Hospital is testing the detection of type, location and severity of a stroke using machine learning",Oregon Health and Science University~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,Google~Google Research detects diabetic eye disease as well as leading ophthalmologists with machine learning,SocialEyes~SocialEyes diagnoses diseases in places where doctors are scarce by scanning the human retina with deep neural networks at the edge, can detect critical head trauma or stroke symptoms from CT scans with more than 95% accuracy using deep neural networks and natural language processing,University of Nottingham~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,"Danish Emergency Services~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 ",Stanford University~Stanford University Medical uses deep convolutional neural networks to predict skin cancer as well as dermatologists,University of Alberta~The University of Alberta and IBM can predict schizophrenia with 74% accuracy by looking at images of the brain's blood flow,Stanford University~Stanford University Parker Institute for Cancer Immunotherapy predict childhood leukemia patients relapse with 85% accuracy using machine learning,Stanford University~Stanford University trained deep neural networks to predict skin carcinomas from images with the same accuracy as determatologists,Mayo Clinic~Mayo Clinic researchers accurately diagnose hyperkalemia using a smartphone electrocardiogram device,London Hospital for Tropical Diseases~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 ,IDx~IDX launched the first FDA approved artificial intelligence service that can diagnose the eye disease diabetic retinopathy without a clinician's involvement,University College London Hospitals~UCLH plans to use machine learning to triage patients in A&E and better predict demand for the service,"Capitol Health~Capitol Health improves accuracy of diagnosis from scans, X-rays etc using deep learning", achieves 90% accuracy using deep learning to diagnose pulmonary consolidation in chest x-rays,New York University ~NYU researchers detected lymphedema with 93.8% accuracy using neural networks,The University of Texas MD Anderson Cancer Center~Researchers propose a new method for automating the contouring of high-risk clinical target volumes using neural networks,Seoul National University College of Medicine~Researchers in South Korea demonstrate accuracy of 98.8% in diagnosing Parkinson's disease using convoluted neural networks,Google~Google's Verily prioritizes patients by diagnosing retinopathy more accurately than ophthalmologists using deep neural networks,'s deep learning solution which automatically detects strokes from CTA scans reducing detection time from 66 to 6 minutes has earned FDA approval,University of Washington~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,Imagen Tech~Imagen Tech's Osteodetect platform which uses deep learning to detect wrist fractures has acquired FDA approval,DeepMind~DeepMind achieves human specialist accuracy in diagnosing retina disease based on scans using machine learning,National University of Singapore~National University of Singapore researchers use deep learning to outperform current methods in detecting glaucoma progression in patients ,Imperial College London~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,University of Colorado Boulder~Researchers aim to identify fibromyalgia patients from fMRI images using machine learning,Macau University of Science and Technology~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,Niramai~Niramai develops screening tool that improves breast cancer diagnosis using machine learning ,Government of Japan~Japan to automate patient information entry and some medical procedures by investing in 10 AI-powered hospitals ,"Unanimous AI~Unanimous AI achieves 22% more accurate pneumonia diagnoses with the use of ""swarm intelligence""",DeepMind~DeepMind aims to improve machine learning system to detect breast cancer from images with more diverse dataset,Enlitic~Enlicit classifies malignant tumours with 50% better accuracy than humans and 0 false-negatives with deep learning,"Enlitic~Enlitic augments radiologists to achieve 21% faster, 11% more sensitive and 9% more specific reading of fractures in X-rays with deep learning",Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital~Scientists automate detection of polyps during colonoscopy using deep learning,University of Toronto~University of Toronto aims to early detect individuals at risk for clinical decline with the use of machine learning,PlantVillage~PlantVillage detects multiple diseases in Cassava plants with machine learning,Anglia Ruskin University~Anglia Ruskin University researchers develop mobile system which detects tuberculosis with 98.4% accuracy,Osaka University~Researchers at Osaka University differentiate between different types of cancer cells using a convolutional neural network,Aravind Eye Hospital~Aravind Eye Hospital identifies eye complications arising from diabetes with a 97.5% accuracy using machine learning ,Infervision~Infervision successfully annotates lung nodules in scans using machine learning,Novartis~Novartis researchers train algorithm to identify different cell types to spot cancer in scans,Stanford University~Researchers at Stanford University identify depression in patients with 80% accuracy using machine learning,Baidu~Baidu builds automated cat shelter for strays using image recognition, University of Southern California~University of Southern California researchers determine an efficient combination of tests to accurately predict FASD in children,MIT~MIT researchers propose an efficient and accurate system for protecting privacy in healthcare datasets,Imperial College London~Imperial College Researchers diagnose ovarian cancer patients with survival rates under 2 years,University of California Los Angeles~Researchers at UCLA develop a convolutional neural networks system that detects prostate cancer as well as experienced radiologists in detecting prostate cancer,New York University ~New York University and IBM Research to assess the presence of glaucoma in the retina using deep learning



Healthcare Providers And Services

Data Sets

Structured / Semi-structured,Audio,Images,Time series

AI Technologies

Potential Vendors

inferVISION,inferVISION,IBM Watson,SocialEyes,,Corti,IBM Watson,Alivecor,Motic,Alan Turing Institute,Enlitic,Google,DeepMind Technologies,Unanimous AI,PathAI,IBM Research