Truace
Subscribe
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
Show filters and sorting

The board · page 8 of 20

211
Evidence-backed gainPeer-reviewedBusiness

The accuracy of the system was validated via twice-weekly manual cycle count. The model uses artificial intelligence and various algorithms to recommend inventory optimizations based on transaction data and notably requires no electronic health record integration.

Source article: Implementation of a passive bin-based perpetual medication inventory model within ambulatory clinics at an academic medical center

American Journal of Health-System Pharmacy
Reader signal

How should this claim be treated?

212
Evidence-backed gainPeer-reviewedHealth

Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study: In internal validation (Stage I), it achieved an accuracy of 0.980 (95% CI 0.977-0.983) and an ROC-AUC of 0.995 (95% CI 0.994-0.997).

Source article: Artificial intelligence-assisted histopathological diagnosis of endocervical gastric-type adenocarcinoma: a multicenter model development and validation study

The Journal of Pathology: Clinical Research
Reader signal

How should this claim be treated?

213
Evidence-backed gainPeer-reviewedClimate

To enhance prediction accuracy across a broad concentration range, a machine learning model was introduced to develop a high-precision quantitative analysis method for Fe 3+ .

Source article: Machine learning-assisted nitrogen-doped carbon dots for Fe<sup>3+</sup> detection in aqueous environments

Analytical Methods
Reader signal

How should this claim be treated?

214
Evidence-backed gainPeer-reviewedScience

Data-efficient exploration of atomic clusters via uncertainty quantification on complex potential energy surfaces: Furthermore, active learning driven by MCD significantly reduces the computational overhead of first-principles calculations while maintaining high predictive accuracy.

Source article: Data-efficient exploration of atomic clusters via uncertainty quantification on complex potential energy surfaces

The Journal of Chemical Physics
Reader signal

How should this claim be treated?

215
Evidence-backed gainPeer-reviewedHealth

Artificial intelligence-based algorithms improve quantification of breast arterial calcifications detected on screening mammography and strengthen their prognostic value for cardiovascular risk in women.

Source article: [Breast arterial calcifications and cardiovascular risk in women]

Giornale Italiano di Cardiologia
Reader signal

How should this claim be treated?

217
Evidence-backed gainPeer-reviewedScience

Forest kernel balancing that builds kernels from random forest and BART leaf co-occurrence improves computational and statistical performance for balancing covariates in observational causal inference by prioritizing outcome-relevant nonlinearities and interactions.

Source article: Forest Kernel Balancing Weights: Outcome-Guided Features for Causal Inference

Statistics in Medicine
Reader signal

How should this claim be treated?

218
Evidence-backed gainPeer-reviewedHealth

Plasma proteomics XGBoost models with SHAP-selected markers improved discrimination of prevalent osteoporosis and prediction of incident osteoporosis from baseline samples in UK Biobank.

Source article: Explainable Plasma Proteomics-Based Machine Learning for Osteoporosis Diagnosis, Prognosis, and Protein Biomarker Discovery in the UK Biobank

The FASEB Journal
Reader signal

How should this claim be treated?

219
Evidence-backed gainPeer-reviewedHealth

Machine learning and related SMART technologies improved early diagnosis and monitoring of obesity by predicting metabolic risk and automating adipose tissue measurement, and were linked to meaningful weight loss after robotic bariatric procedures.

Source article: Technology and Obesity: A Year in Review

Advances in Therapy
Reader signal

How should this claim be treated?

220
Evidence-backed gainPeer-reviewedHealth

An integrated ligand-based machine learning and structure-based docking funnel screened 22,823 compounds and identified HY-18,623 as a potent dual CDK4/6 inhibitor with low-nanomolar IC50s.

Source article: Harnessing machine learning, docking and molecular dynamics for the virtual screening of compounds as CDK4/6 dual inhibitors

Molecular Diversity
Reader signal

How should this claim be treated?

221
Evidence-backed gainPeer-reviewedHealth

A multimodal deep learning model analyzing resting 12-lead ECG and clinical data was feasible for pre-participation cardiovascular screening and achieved moderate discrimination for fitness for competitive sports.

Source article: Ai-based multimodal analysis of ECG and clinical data for evaluation for competitive sports participation: The VALETUDO trial

International Journal of Cardiology
Reader signal

How should this claim be treated?

222
Evidence-backed gainPeer-reviewedLifestyle

Nine machine learning models using baseline frailty index predicted motoric cognitive risk syndrome, with higher frailty linked to increased MCR risk in adults aged 45 and older.

Source article: The impact of frailty and its changes on the development of motoric cognitive risk syndrome in middle-aged and older adults

Journal of the Formosan Medical Association
Reader signal

How should this claim be treated?

224
Evidence-backed gainPeer-reviewedHealth

A Random Forest model using eight routinely available variables predicted subsequent vasopressor need after two fluid boluses in pediatric suspected sepsis with AUROC 0.827 and stratified patients into four tiers with a 6.6% to 63.6% gradient.

Source article: Development of a machine-learning risk stratification tool for vasoactive medication need after two-bolus fluid resuscitation in pediatric suspected sepsis

Pediatric Research
Reader signal

How should this claim be treated?

225
Evidence-backed gainPeer-reviewedClimate

An integrated source-pathway-receptor framework using XGBoost and SHAP improved differentiation of industrial versus agricultural PTE risks in farmland soils and supported targeted zoned control to avoid excessive remediation.

Source article: Quantitative decoupling of source-pathway-receptor driving mechanisms for integrated soil risk via interpretable machine learning

Environmental Pollution
Reader signal

How should this claim be treated?

226
Evidence-backed gainPeer-reviewedScience

Logistic regression screening model using routine indicators like total protein and hemoglobin achieved AUC 0.843 and provides an accessible tool for early identification of individuals at high risk of M-protein in resource-limited primary care.

Source article: Development and validation of a generalizable M-protein screening model using routine laboratory indicators: a multicenter retrospective study

Clinica Chimica Acta
Reader signal

How should this claim be treated?

227
Evidence-backed gainPeer-reviewedHealth

A CatBoost model integrating 22 granular nursing and emergency department features collected within the first 24 hours improved early in-hospital mortality prediction for acute ischemic stroke patients, achieving higher discrimination than established ICU scores in both internal and external validation.

Source article: An Interpretable Machine Learning Framework with Clinical Nomogram for Predicting In-Hospital Mortality in Acute Ischemic Stroke Using High-Granularity Bedside Data

Journal of Stroke and Cerebrovascular Diseases
Reader signal

How should this claim be treated?

228
Evidence-backed gainPeer-reviewedHealth

TrialScout using a large language model matched registered trials to result publications with 92.5% sensitivity and located publications for 63.6% of a 9,600-trial sample, accelerating locating trial results.

Source article: TrialScout links published results to trial registrations using a large language model

Journal of Clinical Epidemiology
Reader signal

How should this claim be treated?

229
Evidence-backed gainPeer-reviewedHealth

Machine learning models using 7T SWI vascular topology, density and intensity features enabled noninvasive preoperative differentiation of glioma IDH status and WHO grade, with improved performance when integrated with clinical factors.

Source article: Noninvasive Profiling of the Glioma Vascular Microenvironment via 7T MRI: Decoding Angiogenic Signatures for Isocitrate Dehydrogenase and World Health Organization Grade Differentiation

Journal of Magnetic Resonance Imaging
Reader signal

How should this claim be treated?

231
Evidence-backed gainPeer-reviewedHealth

A prespecified EfficientNet plus Random Forest model classified gross pathology photographs to distinguish NIFTP from IEFVPTC with pooled AUC 0.788, sensitivity 0.588 and specificity 0.944 in 87 patients.

Source article: Deep Learning-Based Classification of NIFTP and Invasive Encapsulated Follicular Variant of Papillary Thyroid Carcinoma Using Gross Pathology Images

Journal of Imaging Informatics in Medicine
Reader signal

How should this claim be treated?

233
Evidence-backed gainPeer-reviewedHealth

Automated AI quantification of pulmonary artery-to-vein volume difference achieved the highest discrimination for high/intermediate-high risk acute pulmonary embolism with low missed-diagnosis risk.

Source article: Pulmonary Artery-to-Vein Volume Difference: A New Imaging Biomarker for Risk Stratification in Acute Pulmonary Embolism

Academic Radiology
Reader signal

How should this claim be treated?

234
Evidence-backed gainPeer-reviewedHealth

A three-stage explainable framework that fuses deep representations from multiple pretrained CNNs and classifies them with an RBF-kernel SVM achieved 88% accuracy and 88% F1 for skin lesion classification while adding LIME-based explanations.

Source article: An Explainable Computer-Aided Framework for Skin Lesion Classification Using Deep Learning

Journal of Visualized Experiments
Reader signal

How should this claim be treated?

235
Evidence-backed gainPeer-reviewedScience

Adaptive boosting support vector regression trained on GC parameters predicts retention times with high accuracy, enabling optimization of capillary gas chromatography to separate coeluted C1-C12 hydrocarbon isomers.

Source article: Separation of coeluted compounds in capillary gas chromatography: customization via machine learning retention time prediction

Analytical and Bioanalytical Chemistry
Reader signal

How should this claim be treated?

236
Evidence-backed gainPeer-reviewedHealth

AI-based ICE module created left atrial shell from the right atrium without a pre-ablation mapping catheter and guided pulsed field ablation with 100% acute success and 77.7% paroxysmal and 71.8% non-paroxysmal freedom from arrhythmia at 270 days after blanking.

Source article: AI-ICE Guided Pulsed Field Ablation of Atrial Fibrillation with Variable Loop Circular Catheter

Europace
Reader signal

How should this claim be treated?

237
Evidence-backed gainPeer-reviewedHealth

AI-assisted ultrasound of the rectus femoris quantified intramuscular fat percentage (FATi), which was independently associated with diabetic nephropathy and adverse metabolic profiles in patients with diabetes.

Source article: Intramuscular Fat Assessed by AI-Assisted Muscle Ultrasound: Association With Cardiometabolic Risk Factors and Diabetic Nephropathy in Diabetes Mellitus

Diabetes, Obesity and Metabolism
Reader signal

How should this claim be treated?

238
Evidence-backed gainPeer-reviewedHealth

Stacked ensembles combining five CNN backbones improved automated detection and size stratification of periapical lesions on cropped intraoral radiographs, reaching high accuracy and high sensitivity for very small lesions on internal testing.

Source article: Stacked Ensemble Deep Learning Models for Accurate Detection and Size Stratification of Periapical Lesions on Intraoral Radiographs

Australian Endodontic Journal
Reader signal

How should this claim be treated?

239
Evidence-backed gainPeer-reviewedHealth

Adapted iPsRS model using 13 individual-level SDoH predictors predicted 1-year all-cause hospitalization in a general adult cohort with AUROC up to 0.671, enabling equity-aware risk stratification for clinical care.

Source article: Adaptation of a fair individualized polysocial risk score for hospitalization risk prediction

JAMIA Open
Reader signal

How should this claim be treated?

240
Evidence-backed gainPeer-reviewedHealth

Dynamic class-specific F1-score weighting with ECF1V increased ensemble classification accuracy to 98.25% on Breast Cancer Wisconsin and 89.47% on UCI Heart Disease datasets, outperforming conventional voting under non-linear and imbalanced conditions.

Source article: Dynamic F1-score-based voting strategies for multi-class classification: an adaptive ensemble approach for non-linear and imbalanced datasets

Scientific Reports
Reader signal

How should this claim be treated?