AI Medical Compendium

Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy.

BMC medical informatics and decision making Feb 4, 2026

BACKGROUND: Sepsis-Induced coagulopathy (SIC) is not only a common complication in the development process of sepsis but also related to poor prognosis of sepsis. We aimed to establish a machine learning (ML) model to predict the 28-day mortality ris... read more

Comparative performance of ChatGPT, Gemini, and Deepseek on endodontic exam questions in Turkish and English.

BMC oral health Feb 4, 2026

De novo protein design: a transformative frontier in clinical protein applications.

Journal of translational medicine Feb 4, 2026

BACKGROUND: Protein biologics are indispensable in disease prevention, diagnosis, and therapy, yet their development remains largely constrained by reliance on native protein scaffolds, resulting in long development timelines, limited structural and ... read more

Quantification of interstitial fibrosis in digitized kidney biopsies using deep neural networks.

Diagnostic pathology Feb 4, 2026

Artificial intelligence, machine learning-based automated fibrosis quantification in preclinical models of pulmonary fibrosis.

Respiratory research Feb 4, 2026

Machine learning performance for a small dataset: random oversampling improves data imbalances and fairness.

BMC medical research methodology Feb 4, 2026

Leveraging in-silico deep learning and computational analyses to predict the pathogenicity of ROBO4 variants of uncertain significance in aortic aneurysm and dissection patients.

BMC cardiovascular disorders Feb 4, 2026

Variants of uncertain significance (VUS) in genes implicated in thoracic aortic aneurysm (TAA) present clinical challenges due to ambiguous pathogenicity and low patient representation. This study investigates the pathogenic potential of missense VUS... read more

Validation of an AI model for pediatric myelin maturation age assessment and benefits for junior radiologists.

BMC medical imaging Feb 4, 2026

Association of lactate-to-albumin ratio with 28-day mortality in elderly sepsis patients: a retrospective MIMIC-IV database analysis.

BMC infectious diseases Feb 4, 2026

BACKGROUND: The lactate-to-albumin ratio (LAR) is correlated with mortality in critically ill patients; however, its predictive value for sepsis in the elderly remains underexplored. METHODS: This retrospective cohort study used the data from the MIM... read more

Explainability in AI-enabled medical neurotechnology: a scoping review.

Journal of neuroengineering and rehabilitation Feb 4, 2026

Artificial Intelligence Medical Compendium

Explainable machine learning model for predicting short-term outcomes in sepsis- induced coagulopathy.

Comparative performance of ChatGPT, Gemini, and Deepseek on endodontic exam questions in Turkish and English.

De novo protein design: a transformative frontier in clinical protein applications.

Quantification of interstitial fibrosis in digitized kidney biopsies using deep neural networks.

Artificial intelligence, machine learning-based automated fibrosis quantification in preclinical models of pulmonary fibrosis.

Machine learning performance for a small dataset: random oversampling improves data imbalances and fairness.

Leveraging in-silico deep learning and computational analyses to predict the pathogenicity of ROBO4 variants of uncertain significance in aortic aneurysm and dissection patients.

Validation of an AI model for pediatric myelin maturation age assessment and benefits for junior radiologists.

Association of lactate-to-albumin ratio with 28-day mortality in elderly sepsis patients: a retrospective MIMIC-IV database analysis.

Explainability in AI-enabled medical neurotechnology: a scoping review.

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