Medical Ethics / Professional Responsibility

A comparative evaluation of ChatGPT-assisted and traditional methods of teaching diagnostic assessments to medical students: A randomized controlled study.

The rapid development of artificial intelligence (AI) technology has brought new opportunities and challenges to the ever-evolving field of medical education. However, the specific impact of AI on the teaching of diagnostic assessments to medical students requires further investigation. The purpose of this study was to evaluate the effectiveness of ChatGPT-assisted teaching of diagnoses. Eighty me...

A Reliability-Guided Fusion and Dynamic Dual-Domain Mask-Modulated Shearlet Network for Medical Image Segmentation.

Deep learning methods are becoming increasingly important for medical image segmentation. However, previous approaches often performed poorly in spatial-frequency-domain fusion and feature fusion, leading to inaccurate lesion localization, hazy boundaries, and low accuracy. This paper proposes a reliability-guided fusion and dynamic dual-domain mask-modulated Shearlet network for medical image seg...

Cross-layer semantic alignment and context enhancement network for medical image segmentation.

Medical image segmentation aims to accurately delineate organs, tissues, or lesion regions from complex medical images. However, existing hybrid model...

Privacy-preserving intrusion detection in IoT smart homes using a federated hybrid 1D-CNN-LSTM model with explainable AI.

The proliferation of Internet of Things (IoT) devices in smart home environments has dramatically expanded the attack surface for cyber threats, parti...

Humanoid Colleagues and the Rheumatology Workforce: Preparing for a New Era.

Rheumatology faces sustained workforce strain, widening access gaps, and escalating administrative burden. Fellowship expansion and integration of adv...

Ethics and Professionalism in Artificial Intelligence and Medical Practice: A Position Paper From the American College of Physicians.

Artificial intelligence (AI) in health care is being rapidly adopted in perhaps one of the most rapid implementations of technology in medicine to dat...

Boundary-aware data augmentation for solid waste hydrothermal carbonization: An uncertainty-guided SMOTE framework.

Hydrothermal carbonization (HTC) plays a crucial role in sustainable organic solid waste conversion for mitigating energy crises. However, accurate pr...

A novel convolution-transformer model for differentiating hypertrophic cardiomyopathy from Phenocopies using cardiac MRI.

BACKGROUND AND OBJECTIVES: Hypertrophic Cardiomyopathy (HCM) is the most prevalent inherited cardiomyopathy. Its left ventricular hypertrophy (LVH) ph...

Dendritic U-Net for robust vascular wall segmentation in ultrasound imaging.

PURPOSE: We proposed a method that combines the deep learning model U-Net with a dendritic neuron model (DNM) and demonstrated its effectiveness for m...

An artificial intelligence and numerical simulation-based strategy for multi-objective optimization of hemodynamics in curved vessels.

Understanding and optimizing blood flow behavior in curved vessels is crucial for improving cardiovascular treatment planning and reducing complicatio...

Large Language Models as a New Tool for Therapists in Internet-Based Cognitive Behavioral Therapy: Blinded Clinician Rating Pilot Experiment.

BACKGROUND: Internet-based cognitive behavioral therapy (iCBT) is an effective and scalable alternative to face-to-face psychotherapy, but its reach i...

CT scan range planning in clinical practice: An international survey of scan range extension, quality assurance, and AI integration.

INTRODUCTION: Computed tomography (CT) scan range planning is a modifiable determinant of radiation exposure but remains highly variable in clinical p...

Projected westward advance of tropospheric formaldehyde over China.

Economic development and population aggregation are driving the east-to-west spread of tropospheric formaldehyde (HCHO) in China; yet the historical t...

[Multi-modal tumor boundary clustering recognition based on artificial intelligence virtual cells and near-infrared surgical field].

In order to accurately identify tumor boundaries and improve diagnostic efficiency, this study proposes a multi-modal tumor boundary identification me...

AI-Assisted Tumor Boundary Delineation via Targeted Ultrasmall Iron Oxide Nanoprobe for High-Contrast HER2-Positive Tumor Imaging.

Breast cancer continues to be a leading cause of cancer-related mortality in women globally, where precise diagnosis and clear tumor demarcation are c...

[A semi-supervised MRI image segmentation dual-network model for regions with ambiguous boundaries and heterogeneous regions].

OBJECTIVES: To construct a high-value region-guided dual-network semi-supervised segmentation method (HVASS) under extremely low labeling rates for ad...

Psychedelics align brain activity with context.

Psychedelics can profoundly alter consciousness by reorganizing brain connectivity1,2, producing acute experiences that shape lasting psychological ch...

A novel medical image segmentation network for colorectal polyp small targets and fuzzy boundaries.

OBJECTIVES: To address the challenges of complex feature variations and unclear boundary definitions between segmented targets and surrounding regions...

Evaluating the impact of segmentation strategies on radiomic feature stability for paediatric brain tumour diagnosis using diffusion weighted imaging.

OBJECTIVES: This research aims to comprehensively assess the impact of both conservatively and extensively delineated Regions of Interest (ROI) on sub...

Acceptability, Usability, and Clinical Appropriateness of an AI-Powered Tool for Linkage to HIV Services After HIV Self-Testing in South Africa: Mixed Methods Evaluation.

BACKGROUND: Timely linkage to HIV prevention and treatment services following HIV self-testing (HIVST) remains a challenge in many countries. While HI...