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Good Space a ranking of the record

TheGood surrounding AI

574 documented gains are on the board. 82% rest on at least one peer-reviewed study, and 8% clear the high-evidence bar. Health carries 49% of it. The latest was filed Oct 16, 2026.

Every gain on the board, one square each, shaded by the strength of its evidence. High 45 Moderate 529 Emerging 0
574 results
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The board · page 7 of 20

182
Evidence-backed gainPeer-reviewedHealth

FedMediFormer-XAI combined federated learning, multimodal transformers, diffusion augmentation and GNN drug recommendation to achieve 94.2% accuracy for diabetes prediction and NDCG 0.91 for personalized drug recommendation while enabling privacy-preserving training without sharing raw patient data.

Source article: FedMediFormer-XAI: Federated Multimodal Transformers with Diffusion Augmentation and Graph-Based Drug Recommendation for Diabetes

Journal of Visualized Experiments
Reader signal

How should this claim be treated?

183
Evidence-backed gainPeer-reviewedHealth

An XGBoost model using 43 routine preoperative variables estimated 1-year mortality after total knee and hip arthroplasty with AUROC 0.761 and stable calibration, stratifying patients so the top 5% had 6.2-fold higher mortality than baseline.

Source article: Advancing preoperative planning technology in total joint arthroplasty with a real-time machine learning calculator: 1-year mortality risk in a value-based care era

Arthroplasty
Reader signal

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184
Evidence-backed gainPeer-reviewedHealth

AI and complementary digital health technologies improved travel healthcare by enhancing pre-travel risk prediction, enabling earlier outbreak detection during travel, and increasing diagnostic accuracy after travel.

Source article: Artificial Intelligence and Complementary Digital Health Technologies Across the Travel Medicine Continuum: A Narrative Review

Journal of Travel Medicine
Reader signal

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185
Evidence-backed gainPeer-reviewedEducation

Among 503 Polish state university students, habit and performance expectancy increased behavioral intention to use ChatGPT, and behavioral intention increased actual use behavior in higher education.

Source article: Students’ Acceptance of ChatGPT in Higher Education: An Extended Unified Theory of Acceptance and Use of Technology

Innovative Higher Education
Reader signal

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186
Evidence-backed gainPeer-reviewedLifestyle

In 230 SMEs, green innovation was positively related to sustainable performance, mediated by green knowledge sharing and green dynamic capabilities, with AI significantly moderating those links.

Source article: Power of Green Capabilities and Artificial Intelligence (AI): Understanding How and When Green Innovation Promotes Sustainability

Business Strategy and the Environment
Reader signal

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187
Evidence-backed gainPeer-reviewedHealth

XGBoost model predicted PMOS status from detailed body-composition measures with AUC 0.701 in testing, with SHAP highlighting regional fat masses as top predictors.

Source article: Causal adiposity and clinical validation of regional fat distribution in PMOS: a multi-modal analysis integrating GBD 2021, Mendelian randomization, and machine learning

International Journal of Obesity
Reader signal

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188
Evidence-backed gainPeer-reviewedHealth

Protocol proposes AI-based DyVe-X software to continuously quantify exertional dyspnoea against work rate and ventilation and to identify excessive and constrained breathing patterns during incremental CPET, with anticipated superior performance over peak breathing reserve criterion.

Source article: A protocol for validation of novel artificial intelligence-based framework for dyspnoea investigation with cardiopulmonary exercise testing

ERJ Open Research
Reader signal

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189
Evidence-backed gainPeer-reviewedHealth

An ensemble deep learning model combining AP and lateral skull X-rays detected skull fractures in neonates and infants with 91.6% accuracy and 0.938 AUC on external validation, improving diagnostic accuracy while reducing need for CT.

Source article: Automated Diagnosis of Infantile Skull Fractures From X-Ray Images Using an Ensemble Deep Learning Model

Journal of Korean Medical Science
Reader signal

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190
Evidence-backed gainPeer-reviewedHealth

Integrating surface-enhanced Raman spectroscopy with a support vector machine model enabled rapid species-level identification of seven clinically common Nocardia spp. at 99.47% accuracy to guide clinical treatment.

Source article: Species-level identification of Nocardia spp. from clinical samples via intelligent analysis of Raman spectroscopic fingerprints

World Journal of Microbiology and Biotechnology
Reader signal

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191
Evidence-backed gainPeer-reviewedScience

Ensemble tree-based machine learning models predicted band gap energies across multiple halide perovskite families with strong accuracy and identified B-site and X-site properties as key descriptors to guide design of new low-toxicity materials for optoelectronics.

Source article: Machine learning insights into band gap properties in halide-based perovskites

Physical Chemistry Chemical Physics
Reader signal

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192
Evidence-backed gainPeer-reviewedHealth

A logistic regression model combining grayscale ultrasound, contrast-enhanced ultrasound, and serum TPO-Ab improved differentiation of benign versus malignant thyroid nodules in Hashimoto's thyroiditis, reaching cross-validated AUC 0.849 with 77.3% sensitivity and 77.8% specificity.

Source article: A Multiparametric Approach Integrating Multimodal Ultrasound and Serum TPO-Ab for Differentiating Thyroid Carcinoma in Hashimoto's Thyroiditis: A Comparative Diagnostic Study with Internal Validation

Journal of Ultrasound in Medicine
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193
Evidence-backed gainPeer-reviewedHealth

Dynamic machine learning models using vital signs, lab trends and unstructured data can detect sepsis-related deterioration hours before clinical decompensation in critically ill cancer patients, supporting a shift from reactive to predictive onco-critical care.

Source article: Artificial intelligence for early sepsis detection and dynamic prognostication in onco-critical care

World Journal of Critical Care Medicine
Reader signal

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194
Evidence-backed gainPeer-reviewedHealth

Automation and AI applied to ventilator management support waveform analysis, asynchrony detection, and weaning-readiness prediction to enable more individualized lung-protective care within predefined safety limits.

Source article: Physiology-guided mechanical ventilation: Monitoring, proportional assist, and bounded automation

World Journal of Critical Care Medicine
Reader signal

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195
Evidence-backed gainPeer-reviewedHealth

NDIB-Sim achieved high-fidelity long-term brain activity prediction from short-term observations with functional connectivity similarity above 0.97 and enabled subject-specific parameters that distinguish Alzheimer's patients from cognitively normal individuals.

Source article: NDIB-Sim: A Multimodal Bidirectional PINN Model for Simulating Brain Dynamics

IEEE Transactions on Neural Networks and Learning Systems
Reader signal

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196
Evidence-backed gainPeer-reviewedCrime

A SnSe/SnO2 p-n heterojunction single-sensor virtual electronic nose using a PCA-KNN framework enables room-temperature, non-contact detection and classification of volatile sulfur compounds released during methamphetamine production and trafficking, with high response to low-concentration H2S and 96.7% accuracy for H2

Source article: SnSe/SnO2 Heterojunction-Based Single-Sensor Virtual Electronic Nose with Low Reaction Barrier for Trace Identification of Volatile Sulfur Compounds toward Illicit Methamphetamine Trafficking Traceability

ACS Applied Materials & Interfaces
Reader signal

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197
Evidence-backed gainPeer-reviewedHealth

GIN-CRC-Pareto improved identification of miRNA-mRNA interactions in colorectal cancer, achieving 0.909 accuracy and 0.969 AUC on binding pair prediction and outperforming existing tools.

Source article: GIN-CRC-Pareto: A graph-based pareto-optimized multi-task learning framework to identify miRNA-target interactions in colorectal cancer

Journal of Biomedical Informatics
Reader signal

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198
Evidence-backed gainPeer-reviewedHealth

H2O AutoML trained on 4713 MESA participants using 21 selected predictors achieved higher discrimination than logistic regression and traditional ML models, reaching AUC 0.882 and accuracy 0.864, intended as a practical tool for clinician risk stratification.

Source article: Improving 10-year cardiovascular disease risk prediction using automated machine learning

International Journal of Cardiology
Reader signal

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199
Evidence-backed gainPeer-reviewedHealth

An ultrasound-based habitat subregional radiomics model using SVM achieved strong external validation for preoperative prediction of invasive breast cancer with concomitant DCIS, supporting preoperative risk stratification.

Source article: Ultrasound Habitat Radiomics for Preoperative Prediction of Invasive Breast Cancer With a DCIS Component: A Dual-center Retrospective Study

Ultrasound in Medicine & Biology
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200
Evidence-backed gainPeer-reviewedPolicy

University EFL students receiving AI-mediated language instruction showed higher English achievement across grammar, vocabulary, reading and writing, plus increased L2 motivation and greater use of self-regulated learning strategies compared to traditional instruction.

Source article: Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning

Frontiers in Psychology
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201
Evidence-backed gainPeer-reviewedHealth

Elastic Net model distinguished three depressive symptom trajectories in older adults with chronic conditions and was deployed as an interactive web-based risk calculator for individualized risk profiling.

Source article: Predicting longitudinal depressive symptom trajectories among older Chinese adults with chronic health conditions: An interpretable machine learning study

International Psychogeriatrics
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202
Evidence-backed gainPeer-reviewedHealth

Interpretable machine learning combining admission D-dimer and total bleeding volume improved prediction of 12-month functional outcome after aneurysmal subarachnoid hemorrhage, with XGBoost achieving AUC 0.904 and combined D-dimer+TBV+Hunt-Hess outperforming single markers, to inform early risk stratification.

Source article: Prognostic Value of Admission D-dimer Levels and Total Bleeding Volume in Aneurysmal Subarachnoid Hemorrhage: A Retrospective Cohort Study with Machine Learning-Based Modeling

Neurocritical Care
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203
Evidence-backed gainPeer-reviewedHealth

A CECT-based 2PI imaging scoring system combined with clinical parameters enabled a Random Survival Forest model to stratify solitary HCC patients into high- and low-risk recurrence groups and predict postoperative recurrence.

Source article: A CECT-Based 2PI System as a Novel Noninvasive Prognostic Tool for Hepatocellular Carcinoma: A Dual-Validation Study

Cancer Science
Reader signal

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204
Evidence-backed gainPeer-reviewedHealth

Cases without consensus were excluded from the AI accuracy analysis. AI accuracy was calculated as the proportion of correct classifications among consensus cases, and the two models were compared using McNemar's test with continuity correction.

Source article: Accuracy of General-Use Multimodal AI Platforms for Pell and Gregory Classification of Impacted Mandibular Third Molars

Cureus
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205
Evidence-backed gainPeer-reviewedHealth

A 17-gene diagnostic signature showed high accuracy for MDS detection (AUC = 0.963). Functional enrichment, machine learning (logistic regression, support vector machine, LASSO), regulatory network (transcription factors, miRNA, RNA-binding proteins, and drug targets), immune infiltration characterization (ssGSEA), and RT-qPCR assessment were performed.

Source article: Integrative bioinformatic analysis delineates a mitochondrial-hematopoietic gene signature for diagnosis and immune characterization in myelodysplastic syndromes

Hematology
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206
Evidence-backed gainPeer-reviewedHealth

Development of a Machine Learning Algorithm for Differential Diagnosis Between Primary Immune Thrombocytopenia and Connective Tissue Disease-Related Thrombocytopenia in Pediatric Patients: Based on the above evaluation indicators, the BPNN model had the best performance, with an F1 score of 0.95, an accuracy rate of 94.87%, and an AUC of 0.9738.

Source article: Development of a Machine Learning Algorithm for Differential Diagnosis Between Primary Immune Thrombocytopenia and Connective Tissue Disease-Related Thrombocytopenia in Pediatric Patients

Journal of Clinical Laboratory Analysis
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207
Evidence-backed gainPeer-reviewedClimate

Explainable AI-Supported Cyber-Physical Collaboration for Sustainable Manufacturing in Industry 5.0: Experimental findings show that the proposed CNN-Transformer architecture achieves 98.5% accuracy and outperforms existing CPHS systems while maintaining low latency.

Source article: Explainable AI-Supported Cyber-Physical Collaboration for Sustainable Manufacturing in Industry 5.0

Journal of Visualized Experiments
Reader signal

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208
Evidence-backed gainPeer-reviewedHealth

Our method outperforms current algorithms in ultrasound PCa data, achieving mean Dice similarity coefficient (DSC), Jaccard similarity coefficient (OMG), and accuracy (ACC) of 83.6 ± 3.1%, 71.8 ± 2.5%, and 83.5 ± 3.1%, respectively.

Source article: A polyline searching-driven evolutionary AI for disease detection of medical imaging data

Physics in Medicine & Biology
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209
Evidence-backed gainPeer-reviewedLifestyle

Explainable and domain-adaptive prediction models for refrigerant charging in air conditioning systems within industrial processes: Validation on six AC sensor datasets demonstrates that AC-RPX achieves state-of-the-art accuracy and F1 scores, significantly outperforming conventional deep learning and domain adaptation baselines.

Source article: Explainable and domain-adaptive prediction models for refrigerant charging in air conditioning systems within industrial processes

Scientific Reports
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210
Evidence-backed gainPeer-reviewedHealth

Methodological Reporting Quality of Artificial Intelligence-Based Orthopedic Studies: A Literature Analysis: Work in this area would benefit from closer attention to generalizability, clinical relevance and the existing reporting guidelines.

Source article: Methodological Reporting Quality of Artificial Intelligence-Based Orthopedic Studies: A Literature Analysis

Medeniyet Medical Journal
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