G Space

The Good surrounding AI

Documented gains, ranked by source quality, corroboration, and recency. Reader feedback is shown separately and never changes the evidence rank. 413 records · page 3 of 14.

Reader signal

How should this claim be treated?

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

Reader signal

How should this claim be treated?

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

How should this claim be treated?

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

Reader signal

How should this claim be treated?

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

Reader signal

How should this claim be treated?

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

Reader signal

How should this claim be treated?

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?

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?

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?

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?

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?

Evidence-backed gainPeer-reviewedOther

Wearable PLF sensors achieved up to 85% accuracy for lameness detection and over 97% accuracy for stress-related physiological changes in extensive sheep systems.

Source article: Precision Livestock Farming Technologies for Sheep Welfare in Extensive Systems: A Comprehensive Review

Veterinary Medicine and Science

Reader signal

How should this claim be treated?

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?

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?

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?

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?

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?

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?

Evidence-backed gainPeer-reviewedHealth

Models trained on routinely collected social care records predicted future hospital admissions and all-cause mortality with meaningful discriminative performance reaching AUROC 0.893.

Source article: Anticipating health and care trajectories from routinely collected social care records

npj Health Systems

Reader signal

How should this claim be treated?

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?

Evidence-backed gainPeer-reviewedScience

Generative AI offers faster and scaled-up foresight that can serve as anticipatory infrastructure for imagining possible futures and foresight solutions.

Source article: ARTIFICIAL INTELLIGENCE AND THE FUTURES TURN: an anticipatory infrastructure for qualitative methods

Qualitative Research in Psychology

Reader signal

How should this claim be treated?

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?

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?

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?

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?

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?

Evidence-backed gainPeer-reviewedHealth

EndoVLM increased visual question-answering accuracy for gastrointestinal endoscopy, raising Kvasir-VQA scores and improving external validation on Gastrovision.

Source article: EndoVLM: A Vision-Language Assistant for Gastrointestinal Endoscopy

Journal of Imaging Informatics in Medicine

Reader signal

How should this claim be treated?

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?

Evidence-backed gainPeer-reviewedPolicy