Latest AI and machine learning research in stem cell research for healthcare professionals.
BACKGROUND: Current guidelines recommend use of adjuvant imatinib therapy for many patients with gastrointestinal stromal tumours (GISTs); however, its optimal treatment duration is unknown and some patient groups do not benefit from the therapy. We aimed to apply state-of-the-art, interpretable artificial intelligence (ie, predictions or prescription logic that can be easily understood) methods o...
BACKGROUND AND AIMS: Lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a pivotal role in the outcome of MASH clinical trials. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artifici...
PURPOSE: To determine if an explainable artificial intelligence (XAI) model enhances the accuracy and transparency of predicting embryo ploidy status ...
Expected to grow at a 5.5% compound annual growth rate and reach a market of $34.6 billion by 2028, the diagnostic radiology market is an innovation p...
BACKGROUND AND OBJECTIVE: Advanced material models and material characterization of soft biological tissues play an essential role in pre-surgical pla...
Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomark...
Advanced Persistent Threat (APT) attacks are causing a lot of damage to critical organizations and institutions. Therefore, early detection and warnin...
Mitophagy serves as a critical mechanism for tumor cell death, significantly impacting the progression of tumors and their treatment approaches. There...
Children with Autism Spectrum Disorder (ASD) show severe attention deficits, hindering their capacity to acquire new skills. The automatic assessment ...
Science journalists, traditionally, play a key role in delivering science information to a wider audience. However, changes in the media ecosystem and...
Artificial Intelligence (AI) and other large language models are rapidly infiltrating the world of education and educational research. These new techn...
This paper is aimed at developing an air quality monitoring system using machine learning (ML), Internet of Things (IoT), and other elements to predic...
Recent breakthroughs in artificial intelligence (AI) language models have elevated the vision of using conversational AI support for mental health, wi...
With the growing application of machine learning models in medicine, principlist bioethics has been put forward as needing revision. This paper reflec...
While the technologies that enable Artificial Intelligence (AI) continue to advance rapidly, there are increasing promises regarding AI's beneficial o...
BACKGROUND AND PURPOSE: Artificial Intelligence (AI) models in radiation therapy are being developed with increasing pace. Despite this, the radiation...
To evaluate the feasibility of using a deep learning dose prediction approach to identify patients who could benefit most from proton therapy based on...
Reinforcement learning (RL), a subset of machine learning (ML), could optimize and control biomanufacturing processes, such as improved production of ...
Tumor heterogeneity is a primary factor that contributes to treatment failure. Predictive tools, capable of classifying cancer cells based on their fu...
Delineating developmental events is central to experimental research using early life stages, permitting widespread identification of changes in event...