The diagnosis of primary ciliary dyskinesia (PCD) can be challenging in patients with mutations in the gene, despite using electron microscopy tomography and ciliary motion analysis. Also, mutational analysis is hindered by a paralogous copy of the ...
BACKGROUND: In an ophthalmology emergency department, determining treatment urgency is crucial for patient safety and the efficient use of resources. The aim of this study was to use artificial intelligence to develop a neural network and evaluate it...
While artificial intelligence's (AI's) potential role in enhancing diagnostic accuracy and personalising treatment is well-recognised, its application in evaluating physicians raises critical ethical concerns as well. The paper examines the impact of...
This paper asks how bioethics navigates, and should navigate, value pluralism in the increasingly global spaces in which bioethics operates. We juxtapose the ethical approaches suggested by East Asian societies, drawing primarily on Confucian ethics,...
The advances in machine learning (ML)-based systems in medicine give rise to pressing epistemological and ethical questions. Clinical decisions are increasingly taken in highly digitised work environments, which we call artificial epistemic niches. B...
People in vulnerable positions who need support in their daily lives often face challenges in receiving timely access to care; for instance, due to disabilities or individual and situational vulnerabilities. There has been an increasing turn to techn...
Automated arrhythmia detection from electrocardiogram (ECG) signals is crucial and important for the early treatment of cardiac disease (CD). In this investigation, eight machine-learning models have been developed to identify improved ECG arrhythmia...
In the era of artificial intelligence (AI), translation education faces pressing challenges to integrate human-machine collaboration into talent cultivation. This study protocol outlines a two-year mixed-methods project that focuses on developing, va...
Brain tumors are the most prevalent and life-threatening cancer; an early and accurate diagnosis of brain tumors increases the chances of patient survival and treatment planning. However, manual tumor detection is a complex, cumbersome and time-consu...
Journal of chemical information and modeling
Dec 14, 2025
Deep learning models show promise for drug response prediction in personalized cancer treatment, but exhibit limited prediction capability for novel drug-cell line combinations due to insufficient coverage of the chemical spaces in training data. The...
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