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Imaging and AI in tertiary prevention of lung cancer: Narrative review and clinical perspectives.

OBJECTIVE: To provide a structured narrative review of current evidence and future directions for artificial intelligence (AI) applications in the tertiary prevention of lung cancer, with a focus on radiology-driven recurrence surveillance, treatment response assessment, prognostic stratification, and real-world clinical implementation. METHODS: A narrative review was conducted using PubMed, Embas...

Hybrid deep learning framework for image restoration in Fso systems affected by log-normal fading.

Image degradation caused by noise and atmospheric fading poses a significant challenge to the reliability and performance of image transmission systems, particularly in Free Space Optical (FSO) communication employing high-order modulation schemes like Quadrature Amplitude Modulation (64-QAM). In such systems, log-normal fading is a result of atmospheric turbulence can severely degrade image quali...

A step-by-step guide for implementation of virtual surgical applications and patient data centralization: practical experience and lessons learned.

BACKGROUND: The expansion of digitalization in the pre-, intra- and post-operative surgical phases allow the development and integration of advanced t...

Leveraging large language models on free-text symptoms from participatory surveillance enhances pertussis forecasting in the United States.

BACKGROUND: Declines in childhood vaccination in the U.S. have contributed to a resurgence of vaccine-preventable diseases, including a notable increa...

Divergent neuropsychiatric and systemic toxicity profiles of abemaciclib and palbociclib: a triangulation study integrating pharmacovigilance, genetic epidemiology, and multi-omics profiling.

Cyclin-dependent kinase 4/6 inhibitors improve outcomes in hormone receptor-positive, human epidermal growth factor receptor 2-negative advanced breas...

Examining the utility of digital phenotyping for the prediction of intrusive experiences.

Background: Intrusive experiences related to witnessing a traumatic event are the core symptom of post-traumatic stress disorder (PTSD), and have been...

The formation mechanism and regulation of the unique flavor in fried dough products.

The distinctive aroma of fried flour-based products results from synergistic high-temperature reactions, primarily the Maillard reaction and lipid oxi...

Raltegravir Plasma Exposure: A Machine Learning-Based Model for its Prediction Using Limited Sampling Strategy.

Recent studies have applied machine learning (ML)-based limited sampling strategies (LSS) to predict drug exposure (AUC), achieving low prediction err...

A framework for quantifying and leveraging uncertainty in pre-trained CT denoising model.

OBJECTIVE: To develop an architecture-agnostic framework that estimates, calibrates, and leverages total uncertainty (aleatoric + epistemic) in pre-tr...

Cybersecurity in Healthcare: A Systematic Review and Narrative Analysis.

BACKGROUND: Cybersecurity attacks in healthcare have increased in number and severity over the last decade. Healthcare targets are ten times more valu...

Early identification of high-risk individuals for mortality after lung transplantation: A retrospective cohort study with topological feature engineering.

Lung transplantation remains the only definitive treatment for end-stage respiratory failure; however, it has substantial post-operative mortality ris...

When AI Colludes: Clinical Reliability of Training and Preference Data as a Trustworthy-AI Criterion.

BACKGROUND: Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophanc...

Getting ahead of sudden cardiac arrest in pediatric hypertrophic cardiomyopathy patients.

INTRODUCTION: Sudden cardiac arrest (SCA) remains one of the most devastating complications of pediatric hypertrophic cardiomyopathy (HCM). Despite ma...

Explainable and visualizable machine learning model development and validation for 5-year postoperative survival prediction in prostate cancer patients aged ≥ 65 years.

BACKGROUND: Machine Learning (ML) models have achieved outstanding performance in predicting post-surgical survival. However, the "black-box" nature o...

Assessment of the Performance of Siemens Scopio Digital Morphology on Bone Marrow Aspirates in Onco-Hematology.

OBJECTIVES: Digital morphology (DM) systems assisted by artificial intelligence are increasingly being introduced into hematology laboratories; howeve...

An Integrated Clinical-Histopathologic Prediction Model for Cardiac Allograft Rejection: Translating Machine Learning into Clinical Risk Frameworks.

BACKGROUND: Cardiac allograft rejection (CAR) remains the leading cause of early graft failure after heart transplantation (HT). Current diagnostics, ...

Clinical Significance of Biomarkers in Oropharyngeal Squamous Cell Carcinoma: Recurrence Prediction and Treatment Response.

BACKGROUND: Oropharyngeal squamous cell carcinoma (OPSCC) accounts for a substantial proportion of head and neck cancers, with a rising incidence larg...

Unsupervised Machine Learning Drives Dynamic Alignment Classification In Navigated Total Knee Arthroplasty.

BACKGROUND: Current classifications used for total knee arthroplasty (TKA) are static and fail to capture the dynamic behavior of the limb during gait...

AI for Hospital Infection Prevention and Control: Real-World Implementation, Impact, and the Gap Beyond Model Development.

BACKGROUND: Artificial intelligence and machine learning (AI/ML) may strengthen hospital infection prevention and control (IPC) through automated surv...

Does the Timing of USMLE Step 1 Affect Performance? A Comparison of Pre- and Post-Clerkship Timing in the Pass/Fail Era.

In 2022, Step 1 of the United States Medical Licensing Examination transitioned to pass/fail scoring, removing a major performance-oriented incentive ...