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All Healthcare AI Use Cases
Accelerate data integration from multiple sourcesAccelerate drug discovery by automating research stages and data integration and analysisAccelerate identity verification for new and existing customersAlerting and diagnostics from real time patient dataAllocate access to public goods such as healthcare for individualsAnalyse and understand customer sentiment displayed through direct customer contactAnalyse biomarkers such as genes for medical potentialAnalyse body or breath odour to diagnose potential diseaseAnalyse clinical outcomes to adapt clinical trial designAssess compatibility of employees or candidates to form efficient teamsAssist hearing impaired people by translating to and from sign languageAssist physicians by diagnosing and providing the latest medical information about rare conditionsAssist visually impaired people by describing images or reading textAssisted or automated diagnosis and prescriptionAutomate building systems to reduce energy costs through AI powered adaptive temperature and energy controlAutomate coding of treatments for billing and administrationAutomate cybersecurity systemsAutomate protection of privacy in mapping data generation processesAutomate tumour contour definitionCapture 3rd party or internal data for price comparison and supplier relationship overviewCensor user generated content on social media and other platformsCreate new productsDetect potential medical events from wearable sensor data and signal emergency responseDevelop enhanced or new insurance proposition based on monitoring actual behavioursDiagnose disease based on physical behaviourDiagnose emotional reaction to enhance customer experienceDiagnose injury like brain trauma from visual scansDiagnose known diseases from scans, images, biopsies, audio and other dataDigitise and automate processes using Robotic Process Automation (RPA)Enable image analysis or GCMS analysis in a high throughput mannerEnable self-learning option generation in CAD softwareEnhance doctors surgical skills with roboticsEnhance individual mobility through use of automated equipmentEnhance individual physical support during therapy and rehabilitationEvaluate medical practitioner performance and provide feedbackIdentify candidates for trial recruitmentIdentify creature characteristics to assist in disease controlIdentify disease via biopsyIdentify fraud, waste, and abuse patterns from clinical and operations dataIdentify health insurance claims that were inappropriately denied by insurance companiesIdentify potential medical insurance fraudIdentify risk of disease via real time sensorsIdentify risk of hospital acquired infections such as sepsisIdentify risk of surface visible disease via camera phoneIdentify target patient subgroups that are underserved or underdiagnosedIdentify the right match for transplant patients and donorsImprove audio qualityImproving construction process quality by detecting errorLeverage molecule database with metabolic stability data to elucidate new stable structuresManage cybersecurity threats and regulatory reportingManage electronic patient health recordsMatch patients with the right doctor for insurance purposesMinimise compute resource requirements in portable devicesMonitor and advise on key health indicators during pregnancyMonitor and react to health symptoms in post-hospitalisation care programmesMonitor patient outcomesMonitor patient prescription complianceMonitor vital signs through CCTV to detect abnormalitiesMonitor, measure and manage staff skills performance based on feedback from robotic assisted surgeryNavigate, extract relevant information and automate interaction with legacy software systemsOptimise clinical trial design including patient selectionOptimise mobile job schedulingOptimise resource allocation in drug development using disease trends and other dataOptimise staff and resource planningOptimise staffing and labour resource allocation to reduce healthcare bottlenecksOptimise supply chainPersonalise messaging, incentives and media used to improve wellness and prescription adherencePersonalise public services to target individual citizens depending on situationPersonalised messaging to improve wellness and patient management for treatment of chronic conditionsPredict and support strategies to minimise risk of sporting injuriesPredict cybersecurity risksPredict energy demand trends based on data sources ranging from sensors to social mediaPredict hazardous locations and establishments based on open source dataPredict individual hospital admission rates using historical and real-time dataPredict likelihood of recividism or criminal activity on an individual basisPredict optimal medication type and dosagePredict outcomes from fewer or less diverse experiments to reduce research costs and time to marketPredict patient mortality to provide appropriate supportPredict personalised health outcomes to recommend individual treatment approachPredict physician attrition riskPredict physiologically acceptable states for discharge from Pediatric Intensive Care UnitPredict population health patternsPredict potential adverse effects when drugs taken are combinedPredict potential staffing requirements to optimise resourcingPredict prescription addiction and abusePredict risk of condition developing at an early stagePredict risk of long term ailment from environmental and real time dataPredict risk of long term diagnosis of disease such as heart attacksPredict risk of patient readmissionsPredicting prescription adherence with different approaches to reminding patientsPrioritise claims review in healthcare insurancePrioritise research and development projectsProduce more accurate and personalised medical implantsProvide first line of medical advice online through chatbotProvide mobility assistance to visually impaired peopleRe-examine data from historic research to discover new applicationsRecognise predictors of emergency mental health interventionRecognise unstructured text, e.g. handwriting, in documents to extract information to streamline processes like account creation, loan and insurance origination and documentationRecommend lifestyle improvements to consumer for insurance policy coverage through robo advisorRecommend personalised medical treatment based on predictive gene mapping
Healthcare Case Studies
AI system predicts risk of diabetes with an 88% accuracy rate in testsAction Against AMD and Benevolent AI aim to find treatments for age-related macular degeneration (AMD) that causes blindness using machine learningAdvisory committee to the National Institutes of Health to identify health needs in search query data in the US using machine learningAmazon announces its Comprehend Medical platform to analyse unstructured medical textsAnglia Ruskin University researchers develop mobile system which detects tuberculosis with 98.4% accuracyAnthem aims to predict the occurrence of allergies using machine learningAravind Eye Hospital identifies eye complications arising from diabetes with a 97.5% accuracy using machine learningAssistance publique – Hôpitaux de Paris optimises staffing by predicting emergency room admission rates by hour and day using machine learningAutonomous Healthcare detects different types of ventilator asynchrony in ICU patients with machine learningBabylon Health claims 82% accuracy for video medical diagnosis based on machine learning and natural language processingBanner Health saves $29m in three years by helping avoid hospitalisation for patients with multiple chronic conditions by remote monitoring of vitals and analysis with machine learningBayer aims to spot drug-associated side effects earlier with the use of machine learning, RPA and natural language processingBeijing Tian Tan Hospital is testing the detection of type, location and severity of a stroke using machine learningBiogen to design individualized treatment plans for newly diagnosed patients with providers using machine learningBlue Cross Blue Shield predicts individual propensity for opioid abuse with 85% accuracy to modify insurance pricing and support appropriate interventions using machine learning analyticsBlue Cross Blue Shield reduced post hospitalisation costs by over 20% by driving patient engagement with digital post care programs using smart devices, sensors and machine learningBlueDot identified Wuhan pneumonia outbreak from social media posts before WHO made public announcement on COVID-19Capitol Health improves accuracy of diagnosis from scans, X-rays etc using deep learningCardiogram detects atrial fibrillation with 97% accuracy surpassing FDA-cleared wearable ECG devices using the Apple Watch and machine learningCenters for Disease Control and Prevention reduce polio report generation time to 1 hour using machine learning to automate regional mapping of the diseaseChildren''s Hospital of Los Angeles predicts when to discharge patients from pediatric intensive care using deep recurrent neural networksCigna to identify at-risk patients from laboratory results and clinical diagnostic data, and offer early treatment options using machine learningCincinnati Children’s Hospital Medical Centre predicted at expert-level 91% accuracy which students are at higher risk of perpetrating school violence using machine learning on interview scoresCleo offers personalised support system for expecting parents which maps user preferences and helps them find matching providers and other services using machine learningCleveland Clinic and Microsoft identify at-risk patients in ICU to prevent the occurrence of cardiac failure with machine learning ensemblesClinicial 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 dementiaDai-ichi Life enhances customer engagement and nudgee them towards healthy habits using app and machine learningDana Farber Cancer Institute accelerates clinical trial recruitment by using machine learning for genome mapping to identify best candidatesDanish 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 learningDeepMind achieves human specialist accuracy in diagnosing retina disease based on scans using machine learningDeepMind aims to improve machine learning system to detect breast cancer from images with more diverse datasetDialogue to optimise emergency rooms triage at Centre hospitalier de l''Université de Montréal (CHUM) using AIDuke University is researching how to predict the onset of Parkinsons by analysing mouse usage with machine learning classifiersDuke University is researching how to predict the onset of neurological disorders such as Parkinsons by analysing Microsoft-Bing search logs using machine-learned classifiersEl Camino Hospital reduces number of patient falls by 39% using machine learning to predict when a patient is about to fallEnlicit classifies malignant tumours with 50% better accuracy than humans and 0 false-negatives with deep learningEnlitic augments radiologists to achieve 21% faster, 11% more sensitive and 9% more specific reading of fractures in X-rays with deep learningFraunhofer Heinrich Hertz Institute and University Medical Center Schleswig-Holstein, a German University Hospital, has developed an algorithm to detect the probability of getting heart attack from ECG and EEG, matching accuracies achieved by cardiologistsGeneral Electric has saved $80 million over the past few years by integrating supplier data across business units using machine learningGold Coast Health saves $3m per annum in operational costs by forecasting patient arrival rates at emergency care using machine learningGoogle Health improves predictions of hospital patient medical outcomes by using deep neural networks trained on 46 billion data pointsGoogle Research detects diabetic eye disease as well as leading ophthalmologists with machine learningGoogle''s Verily prioritizes patients by diagnosing retinopathy more accurately than ophthalmologists using deep neural networksGraphnet detects changes indicative of a seizure in epileptic patients using wearable tracker and machine learning and notifies the patient and carer via appGuangzhou Second Provincial Central Hospital provides initial consultations with conversational robots that can diagnose 200 diseases with 90% accuracyHealthMap analyses social media and publicly available healthcare data to detect and predict outbreaks around the globeHoobox Robotics enables wheelchair users to control the motorized machines through their facial expressionsHuashan Hospital develops a robotics based radiosurgery procedure to treat inoperable intracranial tumour sizes achieving 55% reduction on averageHumana achieves 28-percent increase in customer satisfaction by coaching agents and supervisors in real-time by recognising emotions from customer voiceIBM Health''s Watson for Oncology is criticised for providing inaccurate and potentially dangerous treatment recommendations for cancer patientsIDX launched the first FDA approved artificial intelligence service that can diagnose the eye disease diabetic retinopathy without a clinician''s involvementImagen Tech''s Osteodetect platform which uses deep learning to detect wrist fractures has acquired FDA approvalImperial College London researchers aim at designing a device that will improve dialysis procedure for patients using machine learningImperial College Researchers diagnose ovarian cancer patients with survival rates under 2 yearsInfervision successfully annotates lung nodules in scans using machine learningIntel proposes an automated and proactive healthcare platform to analyse data from wearable devicesIntuitive Surgical enables precise surgeries with smaller and more accurate incisions using robotics by translating surgeon''s hand movements into the instrumentsIsrael Institute of Technology researchers are developing a nano-array to automatically diagnose a number of diseases from exhaled breathJapan to automate patient information entry and some medical procedures by investing in 10 AI-powered hospitalsJohns Hopkins Hospital improves patient monitoring and resource allocation in ER and critical care units in real-time using machine learningKaia Health alleviates back pain with an AI-powered motion tracking and correction technology appKaiser Parmanente increases construction labour productivity by 38% and saves 11% from the initial construction budget with machine vision and analyticsKaiser Permanente predicts probability of rapid deterioration of patient condition and alerts physicians using machine learningKenSci improves on prediction models of mortality risk six months to one year out through deep machine learning leading to better palliative careKing''s College London researchers automate real-time triage of X-ray radiograph reports with high accuracyLondon Hospital for Tropical Diseases is testing an AI powered microscope which detects the presence of malaria parasites in blood with the same accuracy as microscopistsMD Anderson Cancer Center project developing automated cancer treatment recommendation system with IBM Watson failed to deliver and was terminatedMIT AI Lab predicts Alzheimer''s disease before close family members with advanced motion detection and analysis with machine learningMIT researchers aim to make cancer treatments less toxic with machine learningMIT researchers developed a model that could decrease mortality rate of people on liver transplant lists by 20% with machine learningMIT researchers propose an efficient and accurate system for protecting privacy in healthcare datasetsMaria Fareri Children''s Hospital deploys a diagnosis platform using NLP and algorithmic search to assist physicians with difficult to diagnose symptomsMayo Clinic researchers accurately diagnose hyperkalemia using a smartphone electrocardiogram deviceMcGill University predicts signs of dementia two years before its onset with 84% accuracy with supervised learningMercy Hospital Fort Smith improves patient flow and throughput in the ER to improves LWBS rates by over 30% using machine learningMetroHealth predicts patient flow to improve operational decision making using machine learningMetroPath mitigates cyber threats using Darktrace''s network monitoring and machine learningMinneapolis VA Health Care System is researching how to predict the onset of neurological disorders analysing computer usage and car driving patterns with machine learning classifiersNCI designated cancer centers reduces time to treatment for diagnosed patients by 5 days using machine learning and natural language processingNHS investigates whether inflammation plays a role in mental illnesses by extracting blood test results from unstructured medical records with advanced natural language processingNHS trials a platform to improve workplace team efficiency and capabilities using machine learning to predict best courses of actionNYU researchers detected lymphedema with 93.8% accuracy using neural networksNational University of Singapore researchers use deep learning to outperform current methods in detecting glaucoma progression in patientsNatividad Medical Center reduces time to see doctor by 20% and left without being seen rates by 42% by optimising patient flow and resource allocation in ERNew York University and IBM Research to assess the presence of glaucoma in the retina using deep learningNiramai develops screening tool that improves breast cancer diagnosis using machine learningOlive navigates old healthcare software systems using RPA and machine learningOregon 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 opthalmologistsOrlando Health pilots platform to identify patterns in denied health insurance claims to recover payments and avoid future denialsPLA General Hospital in Beijing is using an algorithm for predicting if patients will wake up from a comaPartners HealthCare is developing a new AI tool that predicts the risk of hospital readmissions within 30 days for patients with heart conditionsQure.ai achieves 90% accuracy using deep learning to diagnose pulmonary consolidation in chest x-raysQure.ai can detect critical head trauma or stroke symptoms from CT scans with more than 95% accuracy using deep neural networks and natural language processingResearchers aim to identify fibromyalgia patients from fMRI images using machine learningResearchers at Ben-Gurion University of the Negev are developing a system to monitor cybersecurity threats for medical equipmentResearchers at Cornell University are using deep learning to develop dental restorations with better accuracy than human eyeResearchers at Florida State University predict one-year mortality rate in ICU patients suffering from a heart diseaseResearchers at Harvard University detect genetic defect associated with cancer with the use of AIResearchers at Harvard University predict tuberculosis'' resistance to first-line and second-line drugs with 94% accuracy and 90% accuracy using machine learningResearchers at NYU predict hospital readmission rated by modelling patient notes using natural language processing