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Ada was significantly more accurate in the recognition of inflammatory rheumatic diseases (IRD) than physicians (70% vs physicians' 54%), which included experienced rheumatology physicians

Ada was more accurate than physicians in suggesting the correct final diagnosis (54% of cases vs physicians' 32%)

Highlights the potential of using symptom checkers early in the patient journey and the advantages of considering complete patient information to establish a correct diagnosis.

Shows the potential of symptom checkers to make accurate triage and diagnostic decisions in rheumatology.

Comparison of physician and artificial intelligence-based symptom checker diagnostic accuracy

Real-world hospital ED study of 378 patients, comparing the safety of Ada’s urgency advice to that of the Manchester Triage System (MTS). 

Ada demonstrated a high rate of safety (94.7%) over all medical specialties of the Emergency Department, with a focus on Internal Medicine, Orthopedics and Trauma, and Neurology.

From the 3 lowest MTS categories, 43.4% could have safely accessed lower urgency care such as seeing a GP or managing their symptoms at home.

Ada has the potential to relieve pressure on Emergency Departments by guiding patients to lower urgency care if used at home.

Safety of Triage Self-assessment Using a Symptom Assessment App for Walk-in Patients in the Emergency Care Setting: Observational Prospective Cross-sectional Study

Protocol for first-of-type clinical study set in a Tanzanian district hospital outpatient clinic to investigate the usefulness of symptom assessment applications in LMICs.  

Evaluation of Ada's compared to gold-standard differential diagnoses and triage advice for participants with various conditions and age groups, including children. 

Study protocol for a pilot prospective, observational study investigating the condition suggestion and urgency advice accuracy of a symptom assessment app in Sub-Saharan Africa: the AFYA-'Health' study

Ada’s DDSS prototype could support doctors’ decision-making by showing them new pathways and potential diagnoses.

Ada provided accurate decision support in the clinical inpatient setting for people presenting with dyspnea.

Prospective feasibility study of a novel Diagnostic Decision Support System (DDSS) for medical professionals.

Protocol for a clinical study that is set in a Tanzanian district hospital outpatient clinic to investigate the usefulness of a prototype diagnosis decision support system (DDSS) in the hands of a mid level healthcare worker.

The diagnostic accuracy and qualitative data on the usability, usefulness, and acceptance of the prototype DDSS will provide insights on the appropriateness of the prototype DDSS interface

Investigating the Potential for Clinical Decision Support in Sub-Saharan Africa With AFYA (Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania): Protocol for a Prospective, Observational Pilot Study

Ada supported conversation and improved rapport for 90% of patients, 73% of physicians, and 100% of nurses. 

Improving emergency department patient-doctor conversation through an artificial intelligence symptom taking tool: an action-oriented design. pilot study.

Using a dataset from 464,547 patients, Ada's CVD risk prediction tool achieved superior performance to several established general CVD risk prediction models

Ada could be used to direct individuals to app-based behaviour change recommendations for risk reduction and guidance.

Actionable absolute risk prediction of atherosclerotic cardiovascular disease: a behavior-management approach based on data from 464,547 UK Biobank participants

Proposals by the EU and FDA have set the regulatory groundwork for algorithm change protocols. The FDA proposals are detailed and actionable but are yet to be finalized. The EU has not yet detailed its plan. The authors recommended the EU set out an approach that is coordinated, actionable, and consultative.   

The public, manufacturers, and medical community should be engaged to inform requirements of algorithm change, with a focus on postmarket surveillance, RWP measurement, clinical evaluation, and labeling.

Algorithm change protocols in the regulation of adaptive machine learning-based medical devices

Ada could decrease the average triage nurse waiting times by 54%.

Optimization of Patient Flow in Urgent Care Centers Using a Digital Tool for Recording Patient Symptoms and History: Simulation Study

Ada could help detect genetic auto-inflammatory disorders, including the important group of Periodic Fever Syndromes.

Currently Available Diagnostic And Therapeutic Approaches In Periodic Fever Syndromes

Retrospective analysis of the diagnostic costs of rare inflammatory systemic diseases and the impact of a prototype Ada as a diagnostic decision support system (DDSS).  

If this Ada DDSS prototype were released, it has the potential to lead to earlier diagnosis and could save between 50% and 70% of diagnostic costs. 

Health economic benefits through the use of diagnostic support systems and expert knowledge

Ada uncovered similar ILI trends to an official German surveillance system and could help identify health trends in countries without population-based monitoring systems.

Novel methods in the surveillance of influenza-like illness (ILI): exploration of data from the symptom assessment app Ada, Germany observational case study.

AI solutions can only improve health outcomes in low-income countries if they are designed and adapted with the needs of the local population in mind

To account for regional differences in incidence and disease presentation, 51 maternal and pediatric health conditions have been optimized in Ada for South Africa

Ada’s content readability score has been reduced from grade 11 to below grade 8 (7.4±0.8) while still maintaining medical accuracy

White-box AI-approach like Ada’s makes it possible to capture the differences in underrepresented populations and low-income countries.

Challenges and solutions in adapting an AI-powered health management tool for South Africa

Ada identified the correct condition in the top 3 suggestions in 83% of cases, compared to the next best of 77%, including Australia-specific scenarios.

63% of Ada’s urgency advice matched the gold standard, compared to the next highest app’s score of 52%

The quality of condition suggestions and urgency advice provided by the Ada symptom assessment app assessed with independently generated vignettes optimized for Australia.

The utility of symptom checkers relies on safety, coverage, and accuracy.

Ada’s advice was safe in 97% of cases, with 99% condition coverage and 70% accuracy for top 3 suggestion fit compared to the competitor average of 38%.

How accurate are digital symptom assessment apps for suggesting conditions and urgency advice?: A clinical vignettes comparison to GPs.

97.8% of patients rated Ada very or quite easy to use, and 12.8% would have delayed their appointment or used lower-intensity care.

Patients’ utilization and perception of an artificial intelligence-based symptom assessment and advice technology in a British primary care waiting room: Exploratory pilot study.

A review of data from 950,000 users found that Ada could help uncover the impact of public health policies like COVID-19 lockdown measures. 

Syndromic surveillance insights from a symptom assessment app before and during COVID-19 measures in Germany and the United Kingdom: Results from repeated cross-sectional analyses.

Ada suggested rare diseases in 4% of 15 million assessments, in line with the population rates.

Just how rare are rare diseases on Ada, a medical symptom checker?

89.25% of Ada’s top suggestions matched the confirmed diagnosis, and 33.3% of participants could have received their rare disease diagnosis in the first documented clinical visit with Ada.

Can a decision support system accelerate rare disease diagnosis? Evaluating the potential impact of Ada DX in a retrospective study.

Digital symptom-based screening tools can substantially reduce the transmission of COVID-19.

Applications like Ada (combined with testing and self-isolation) could prevent an additional 8% of the population being infected.

The Potential of Digital Symptom-based Screening to Reduce the Transmission of SARS-CoV-2: a Modelling Study

Ada had 73% accuracy compared to a 38% all-app average and 97% disposition safety compared to an 83% all-app average.

Accuracy of online symptom checkers and the potential impact on service utilisation.

46.4% of 26,646 Ada symptom assessments were completed outside GP office hours. 

Ada’s recommendations were comparable to triage nurses’.

Use Characteristics and Triage Acuity of a Digital Symptom Checker in a Large Integrated Health System: Population-Based Descriptive Study

Ada could help identify mental health disorders in adults.

Accuracy of a chatbot (Ada) in the diagnosis of mental disorders: Comparative case study with lay and expert users.

Ada was the second-best app out of 24 tested in the ear, nose, and throat discipline.

From symptom to diagnosis-symptom checkers re-evaluated : Are symptom checkers finally sufficient and accurate to use? An update from the ENT perspective.

Ada was the most accurate of the 4 apps tested and was fast and easy to use.

What happened when Pulse tested symptom checker apps.

Ada was ‘by far the best’ app out of the 4 tested, asking clear questions and providing the best condition suggestions.

Can you really trust the medical apps on your phone?

Letter to the Editor on Knitza et al., "Comment on “Accuracy and usability of a diagnostic decision support system in the diagnosis of three representative rheumatic diseases: a randomized controlled trial among medical students”

Letter to the Editor on Hill et al., "Comment on: "The quality of diagnosis and triage advice provided by free online symptom checkers and apps in Australia""

Letter to the editor: Do Dr. Google and Health Apps Have (Comparable) Side Effects? An Experimental Study

Ada could help detect genetic autoinflammatory disorders, including familial Mediterranean fever.

Rare diseases 2030: How augmented AI will support diagnosis and treatment of rare diseases in the future.

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