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Computational screening of antimicrobial peptide analogs targeting AdeB efflux transporter protein in Acinetobacter baumannii associated with multidrug resistance.

Overexpression of the AdeABC efflux pump is crucial in conferring multidrug resistance (MDR) in Acinetobacter baumannii (A. baumannii). Its primary subunit, AdeB, recognizes and pumps out aminoglycosides, carbapenems, and several other classes of antibiotics from the cell, making it an attractive target for drug development. There has been substantial interest in utilizing antimicrobial peptides (...

Association between dynamic digital radiography findings and post-extubation respiratory deterioration: A retrospective exploratory analysis of a prospectively collected ICU cohort.

INTRODUCTION: Dynamic Digital Radiography (DDR) is a novel bedside imaging modality that enables real-time visualization of pulmonary motion with minimal radiation exposure. We evaluated whether DDR-derived parameters could assist in stratifying the risk of post-extubation respiratory deterioration in ICU patients. METHODS: We analyzed a prospectively collected, single-center cohort of consecutive...

Path beyond the blind end-unravel the imaging spectrum of appendiceal pathologies.

The appendix is involved in a diverse spectrum of inflammatory, infectious, benign, and malignant conditions that extend far beyond acute appendicitis...

From black box to glass box: explainable artificial intelligence for acute kidney injury prediction-a scoping review and the GLASS-AKI translational framework proposal.

BACKGROUND: Artificial intelligence models for acute kidney injury (AKI) prediction achieve strong discriminative accuracy, yet clinical adoption rema...

Pilot of a blended learning model on medical students' communication skills in the context of digital innovations.

BACKGROUND: Effective physician-patient communication is essential for high-quality medical care. However, digital transformation and the increasing u...

Beyond Validation: Operationalising Post-Deployment Surveillance of AI Medical Devices in Clinical Practice.

Artificial intelligence medical devices are increasingly deployed in clinical practice, yet practical approaches to post-deployment monitoring remain ...

Large-scale transcriptomic data mining using explainable XGBoost and SHAP reveals shared biomarkers and molecular mechanisms between type-2 diabetes and triple-negative breast cancer for drug repurposing.

Type 2 diabetes (T2D) is considered as a risk factor of triple-negative breast cancer (TNBC). So, there is a significant chance of their co-existence....

Immunologic clustering of donor-specific antibodies and clinical outcomes in kidney transplant recipients.

BACKGROUND: Donor-specific antibodies (DSA) against human leukocyte antigens (HLA) are associated with increased immunologic risk in kidney transplant...

High-throughput signal detection of hepatotoxic drug-drug interactions in hospitalized elderly patients: an NLP-driven pharmacovigilance study.

BACKGROUND: Elderly patients are highly susceptible to drug-drug interaction (DDI)-induced liver injury, yet comprehensive real-world evidence remains...

Applying machine learning to pharmacovigilance data: A proof-of-concept study.

AIM: Machine learning (ML) applications in pharmacovigilance remain limited and underexplored. Using data from the French National pharmacovigilance d...

Post-Pandemic Forecasting of Pediatric Acute Respiratory Infections with Deep Learning: A Multi-Pathogen, Multi-Time-Horizon Study.

BACKGROUND: Acute respiratory infections (ARIs) remain a major cause of morbidity and hospitalization in children worldwide. In the post-COVID-19 era,...

The voice of decompensation: an explainable machine learning approach to assessing heart failure severity.

AIMS: Heart failure (HF) is characterized by high morbidity and frequent hospital readmissions, highlighting the need for scalable out-of-hospital mon...

Artificial intelligence in urology: A review of United States Food and Drug Administration-cleared devices.

OBJECTIVE: To systematically characterise United States Food and Drug Administration (FDA) authorised urology-specific artificial intelligence (AI)-en...

Application of Language Models for the Analysis of Adverse Drug Events in Pharmaceutical Research and Development: Scoping Review.

BACKGROUND: Adverse drug events (ADEs) remain a critical safety issue in pharmaceutical research and development (Pharma R&D), necessitating robust me...

A donor-recipient ranking model to optimize long-term survival post liver transplant.

Liver transplant (LT) is a life-saving treatment for patients with cirrhosis and/or hepatocellular carcinoma (HCC), but organ shortages and suboptimal...

Drug-induced multisystem syndromes: An overlooked challenge in pharmacovigilance.

BackgroundDrug-Induced Multisystem Syndromes (DIMS) represent a clinically significant yet under-recognized group of delayed immune-mediated adverse d...

Deep Learning-Based Prediction of Heart Failure Readmission Using Longitudinal Cardiac Device Data.

BACKGROUND: Heart failure (HF) is a leading cause of hospitalization and readmission. Cardiac implantable electronic devices (CIEDs) continuously capt...

Explainable AI for diabetic retinopathy detection using vision transformers.

The heterogeneous acquisition, variability of orientation, and subtle lesions continue to challenge the screening of diabetic retinopathy through colo...

Fusion prediction model for post-ERCP pancreatitis under NSAIDs prophylaxis.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is a common procedure for treating biliary and pancreatic disorders; however, it is ...

Longitudinal validation of ENLIGHT, an AI predictor of immunotherapy response and resistance, in pan-cancer cohorts.

Artificial intelligence (AI) algorithms such as ENLIGHT and DeepPT represent promising approaches to identify predictive biomarkers for immune checkpo...