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Good Space a ranking of the record

TheGood surrounding AI

278 gains match this view. 97% rest on at least one peer-reviewed study, and 3% clear the high-evidence bar. The latest was filed Oct 16, 2026.

Every gain in this view, one square each, shaded by the strength of its evidence. High 9 Moderate 269 Emerging 0
278 results
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Sector: health

Matching records · page 1 of 10

1
Evidence-backed gainPeer-reviewedHealth

AI collected patient histories more effectively than general practitioners during initial consultations, with stronger performance in older patients and for allergies and family history of cancer.

Source article: Performance of artificial intelligence in the collection of patient history in general practice

Journal of Clinical Medicine of Kazakhstan · Drug Safety
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2
Evidence-backed gainPeer-reviewedHealth

AI and large language models have matured to improve clinicians' diagnostic decision-making during bedside and clinic consultations and help institutions increase diagnostic safety, addressing preventable diagnostic errors.

Source article: Can AI assist in reducing diagnostic error? A narrative review

Cell Reports Medicine · Diagnostics
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4
Evidence-backed gainPeer-reviewedHealth

AI-powered systems improved healthcare delivery efficiency and accuracy through personalized medicine, early disease detection, and predictive analytics, while telemedicine expanded access in underserved areas.

Source article: Revolutionizing healthcare and medicine: The impact of modern technologies for a healthier future—A comprehensive review

European Journal of Medical Research · Pharmaceutics
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5
Evidence-backed gainPeer-reviewedHealth

AI chatbots used as supplementary mental health support reduced psychological distress among adolescents aged 10-24 and helped overcome stigma-related barriers to care access.

Source article: The Impact of Chatbots on Adolescent Mental Health Development: A Comprehensive Literature Review

JMIR Mental Health · Journal of Medical Internet Research
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6
Model-prefilled gainPeer-reviewedHealth

AI-enabled hierarchical medical system increased hypertension control target achievement from 68% to 82% and achieved health data accuracy exceeding 95% for chronic disease patients.

Source article: Implementation of an AI-driven hierarchical medical system for chronic disease management: ethical framework, resource optimization, and effectiveness evaluation

Frontiers in Public Health · Acta Balneologica
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8
Model-prefilled gainPeer-reviewedHealth

Generative AI that generates computer-based summaries of patient details improved efficiency, reduced cognitive burden, and standardized information transfer during nurse-to-nurse handoffs from the emergency department to inpatient units.

Source article: A Nurse Hackathon: Improving Effective and Timely Nurse Handoffs Through Use of Generative Artificial Intelligence

CIN: Computers, Informatics, Nursing · Learning Health Systems
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10
Evidence-backed gainPeer-reviewedHealth

A gradient boosting machine model gave interpretable, individualized early BPD risk estimates for preterm infants using routinely available clinical variables, with internal AUC of 0.880.

Source article: Improving early risk stratification for bronchopulmonary Dysplasia in preterm infants using machine learning: development and external validation

Annals of Medicine
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11
Evidence-backed gainPeer-reviewedHealth

In 20 test patients, a hybrid deep learning planning system produced deliverable cervical cancer IMRT plans within 3 minutes while lowering dose to the bladder and small intestine.

Source article: A hybrid deep learning framework for automated treatment planning in cervical cancer radiotherapy

Journal of Applied Clinical Medical Physics
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12
Evidence-backed gainPeer-reviewedHealth

At three Indian tertiary cancer centres, oncologists using OneRx.AI reached clinical recommendations far faster, with high expert-rated accuracy, safety and guideline concordance.

Source article: Prospective multicentre expert evaluation of an artificial intelligence-based oncology clinical decision support system across major cancer types in India

International Journal of Medical Informatics
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13
Evidence-backed gainPeer-reviewedHealth

In five intervention villages, every symptomatic person received a teleconsultation, while only 38.5% of symptomatic people in comparison villages accessed formal healthcare.

Source article: An assisted telemedicine model with digital diagnostics and artificial intelligence-supported clinical decision in hard-to-reach rural communities: a community-based mixed-methods study from Rajasthan, India

Preventive Medicine Reports
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14
Evidence-backed gainPeer-reviewedHealth

A CatBoost model using six simple indicators screened for rapid FEV1 decline with high sensitivity and a useful negative predictive value among Chinese COPD patients with follow-up spirometry.

Source article: Identification of clinical phenotypes and development of a predictive model for rapid lung function decline in COPD patients

Annals of Medicine
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15
Evidence-backed gainPeer-reviewedHealth

A multilayer perceptron using eight clinical, laboratory, and intraoperative predictors estimated early complication risk after prostatectomy, and an online calculator could help flag high-risk patients right after surgery.

Source article: Development and external validation of an explainable machine-learning model for early complications following robot-assisted radical prostatectomy: a multicenter study

Journal of Robotic Surgery
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16
Evidence-backed gainPeer-reviewedHealth

Machine learning models trained on routine nursing home assessment data predicted functional decline in residents with type 2 diabetes with high accuracy, pointing to modifiable risk factors for early identification.

Source article: Mental Health and Cognitive Predictors of Functional Decline in Nursing Home Residents with Type 2 Diabetes

Clinical Gerontologist
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17
Evidence-backed gainPeer-reviewedHealth

A neural network built on six predictors including coagulation parameters discriminated difficult from non-difficult single-incision cholecystectomy cases in internal validation, potentially aiding patient selection and surgical planning.

Source article: A Predictive Model Integrating Coagulation Profiles for Preoperative Risk Stratification of Difficult Single-Incision Laparoscopic Cholecystectomy: A Retrospective Cohort Study Based on Explainable Machine Learning

Surgical Laparoscopy, Endoscopy & Percutaneous Techniques
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18
Evidence-backed gainPeer-reviewedHealth

A mixture-kernel support vector machine trained on graph-theory features from emotion-regulation brain regions best distinguished 32 fibromyalgia patients from 30 controls on sensitivity and AUC, suggesting a route to less subjective diagnosis.

Source article: Graph theory-based machine learning for automated fibromyalgia diagnosis using fMRI during an emotional task

PLOS One
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19
Evidence-backed gainPeer-reviewedHealth

A tongue-image framework that identifies seven tongue attributes and models how they interact reached 0.751 accuracy and 0.767 AUC for liver fibrosis risk screening, with results better than the compared graph and multimodal models.

Source article: An expert routing-driven graph framework from tongue multi-task features to liver fibrosis prediction

Engineering Applications of Artificial Intelligence
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20
Evidence-backed gainPeer-reviewedHealth

In Markov models for Costa Rica, using AI as a first reader in breast screening and lung cancer diagnosis was projected to lower costs while increasing quality-adjusted life-years over 10 years.

Source article: Cost-Effectiveness of AI in Breast Cancer Screening and Lung Cancer Diagnostics: A Case Study From Costa Rica

Value in Health Regional Issues
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21
Evidence-backed gainPeer-reviewedHealth

AI can pull latent diagnostic information from routinely acquired cardiac signals, which could improve ischemia detection where noise, operator dependence and incomplete signal capture limit accuracy.

Source article: Artificial Intelligence for Cardiac Ischemia Detection: A Review of Biosensor, Biomarker, and Imaging Applications

Sensors
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22
Evidence-backed gainPeer-reviewedHealth

An agentic generative AI framework produced disease concept and model structure diagrams for breast cancer and a rare disease that were checked against literature and by modelers and clinicians.

Source article: Conceptualising Health Economic Models Using a Graph Retrieval-Augmented, Agentic AI Framework with Human-in-the-Loop Validation: Proof-of-Concept Study

PharmacoEconomics - Open
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23
Evidence-backed gainPeer-reviewedHealth

An automated PET-CT algorithm can measure body composition changes in advanced prostate cancer patients and identify those on systemic therapy who are at risk for muscle wasting.

Source article: An artificial intelligence algorithm characterizes the deterioration of body composition from systemic therapy for patients with advanced prostate cancer

JNCI: Journal of the National Cancer Institute
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24
Evidence-backed gainPeer-reviewedHealth

Gastroenterologists rated ChatGPT-4's Turkish-language answers to common colonoscopy questions highly, with over 70% of ratings at 4 or above in every domain, outperforming Google Bard.

Source article: Large language models' performance in answering common patient questions about colonoscopy: an expert-based evaluation

BMC Gastroenterology
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25
Evidence-backed gainPeer-reviewedHealth

The AWMP deep learning model predicted cervical cancer survival 4.74% better than the mean of four comparator methods and helped identify four prognosis-linked genes and a B-cell subset tied to immune response.

Source article: Cervical cancer survival analysis by integrating multi-omics data through an adaptive weighted deep neural network

Computational Biology and Chemistry
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26
Evidence-backed gainPeer-reviewedHealth

AI-generated synthetic patients reproduced treatment-effect estimates for escalation versus early intensive therapy in MS while preserving privacy, suggesting a way to extend real-world evidence.

Source article: Validation of generative artificial intelligence techniques for synthetic data generation in multiple sclerosis research: A comparison with real-world evidence from the Italian multiple sclerosis registry

Multiple Sclerosis Journal
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27
Evidence-backed gainPeer-reviewedHealth

In a decision-tree model of 100,000 preterm infants, community-based AI-assisted ROP screening had lower lifetime societal costs and more QALYs than telemedicine or bedside screening in both urban and rural China.

Source article: Cost-effectiveness of community-based artificial intelligence screening for retinopathy of prematurity

Journal of Global Health
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28
Evidence-backed gainPeer-reviewedHealth

A causal machine learning model on 155 reconstruction patients pointed to lower preoperative hemoglobin and albumin as potential causal predictors of complications, which may help risk assessment.

Source article: A Machine Learning Model to Predict Complications Following Head and Neck Microvascular Surgery

Laryngoscope Investigative Otolaryngology
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29
Evidence-backed gainPeer-reviewedHealth

In a small pilot, an LLM-driven voice simulator produced virtual patients whose MADRS scores from experienced raters landed close to their preset profiles, suggesting a scalable practice tool.

Source article: Voice-Enabled Virtual Patients for Interactive Training in Standardized Clinical Assessment: Mixed Methods Pilot Study

Journal of Medical Internet Research
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30
Evidence-backed gainPeer-reviewedHealth

In a partitioned survival model, the AI-supported AIDPATH platform came out dominant over both cilta-cel and standard of care for triple-class refractory multiple myeloma from the German hospital perspective.

Source article: Cost-Effectiveness of AI-Powered Decentralized Production for Advanced Therapies in the Hospital-Generated Chimeric Antigen Receptor T-Cell Therapy for Multiple Myeloma From a German Hospital Perspective: Early Health Technology Assessment Study

JMIR Cancer
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