Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
Since its launch, ChatGPT, an artificial intelligence-powered language model tool, has generated significant attention in research writing. The use of ChatGPT in medical research can be a double-edged sword. ChatGPT can expedite the research writing process by assisting with hypothesis formulation, literature review, data analysis and manuscript writing. On the other hand, using ChatGPT raises con...
The United States Medical Licensing Examination (USMLE) has been a subject of performance study for artificial intelligence (AI) models. However, their performance on questions involving USMLE soft skills remains unexplored. This study aimed to evaluate ChatGPT and GPT-4 on USMLE questions involving communication skills, ethics, empathy, and professionalism. We used 80 USMLE-style questions involv...
Deep neural networks have become increasingly significant in our daily lives due to their remarkable performance. The issue of adversarial examples, w...
Recent immense breakthroughs in generative models such as in GPT4 have precipitated re-imagined ubiquitous usage of these models in all applications. ...
Intracerebral hemorrhage is the subtype of stroke with the highest mortality rate, especially when it also causes secondary intraventricular hemorrhag...
PURPOSE: The proposed work aims to develop an algorithm to precisely segment the lung parenchyma in thoracic CT scans. To achieve this goal, the propo...
The application of artificial intelligence (AI) in medical practice is spreading, especially in technologically dense fields such as radiology, which ...
In image classification, a deep neural network (DNN) that is trained on undistorted images constitutes an effective decision boundary. Unfortunately, ...
Changes in behavioral state, such as arousal and movements, strongly affect neural activity in sensory areas, and can be modeled as long-range project...
Accurate segmentation of head and neck organs at risk is crucial in radiotherapy. However, the existing methods suffer from incomplete feature mining,...
Segmenting breast tumors from dynamic contrast-enhanced magnetic resonance (DCE-MR) images is a critical step for early detection and diagnosis of bre...
Deep learning (DL) techniques have seen tremendous interest in medical imaging, particularly in the use of convolutional neural networks (CNNs) for th...
Artificial intelligence (AI)-assisted robotic surgery seems to offer promise for improving patients' outcomes and innovating surgical care. This comme...
Though deep learning-based saliency detection methods have achieved gratifying performance recently, the predicted saliency maps still suffer from the...
Defect inspection is important to ensure consistent quality and efficiency in industrial manufacturing. Recently, machine vision systems integrating a...
During surgery for foci-related epilepsy, neurosurgeons face significant difficulties in identifying and resecting MRI-negative or deep-seated epilept...
Background samples provide key contextual information for segmenting regions of interest (ROIs). However, they always cover a diverse set of structure...
Academic integrity in both higher education and scientific writing has been challenged by developments in artificial intelligence. The limitations ass...
Accurate segmentation of medical images is an important step during radiotherapy planning and clinical diagnosis. However, manually marking organ or l...
. Sliding motion may occur between organs in anatomical regions due to respiratory motion and heart beating. This issue is often neglected in previous...