Stem Cell Research

Personalized Composite Dosimetric Score-Based Machine Learning Model of Severe Radiation-Induced Lymphopenia Among Patients With Esophageal Cancer.

PURPOSE: Radiation-induced lymphopenia (RIL) is common among patients undergoing radiation therapy (RT)' Severe RIL has been linked to adverse outcomes. The severity and risk of RIL can be predicted from baseline clinical characteristics and dosimetric parameters. However, dosimetric parameters, e.g. dose-volume (DV) indices, are highly correlated with one another and are only weakly associated wi...

DeepFace: Deep-learning-based framework to contextualize orofacial-cleft-related variants during human embryonic craniofacial development.

Orofacial clefts (OFCs) are among the most common human congenital birth defects. Previous multiethnic studies have identified dozens of associated loci for both cleft lip with or without cleft palate (CL/P) and cleft palate alone (CP). Although several nearby genes have been highlighted, the "casual" variants are largely unknown. Here, we developed DeepFace, a convolutional neural network model, ...

Novel drug discovery: Advancing Alzheimer's therapy through machine learning and network pharmacology.

Alzheimer's disease (AD), marked by tau tangles and amyloid-beta plaques, leads to cognitive decline. Despite extensive research, its complex etiology...

The Artificial Third: A Broad View of the Effects of Introducing Generative Artificial Intelligence on Psychotherapy.

This paper explores a significant shift in the field of mental health in general and psychotherapy in particular following generative artificial intel...

The advancement of artificial intelligence in biomedical research and health innovation: challenges and opportunities in emerging economies.

The advancement of artificial intelligence (AI), algorithm optimization and high-throughput experiments has enabled scientists to accelerate the disco...

The use of artificial intelligence in induced pluripotent stem cell-based technology over 10-year period: A systematic scoping review.

BACKGROUND: Stem cell research, particularly in the domain of induced pluripotent stem cell (iPSC) technology, has shown significant progress. The int...

PrCRS: a prediction model of severe CRS in CAR-T therapy based on transfer learning.

BACKGROUND: CAR-T cell therapy represents a novel approach for the treatment of hematologic malignancies and solid tumors. However, its implementation...

Unlocking the full potential of mesenchymal stromal cell therapy for osteoarthritis through machine learning-based in silico trials.

Despite the potential of mesenchymal stromal cells (MSCs) in osteoarthritis (OA) treatment, the challenge lies in addressing their therapeutic inconsi...

Psychological and Brain Responses to Artificial Intelligence's Violation of Community Ethics.

Human moral reactions to artificial intelligence (AI) agents' behavior constitute an important aspect of modern-day human-AI relationships. Although p...

Prognostic model incorporating immune checkpoint genes to predict the immunotherapy efficacy for lung adenocarcinoma: a cohort study integrating machine learning algorithms.

This study aimed to develop and validate a nomogram based on immune checkpoint genes (ICGs) for predicting prognosis and immune checkpoint blockade (I...

A dosiomics model for prediction of radiation-induced acute skin toxicity in breast cancer patients: machine learning-based study for a closed bore linac.

BACKGROUND: Radiation induced acute skin toxicity (AST) is considered as a common side effect of breast radiation therapy. The goal of this study was ...

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

This study aimed to compare the accuracy of IFN-τ stimulated gene abundance (ISGs) in peripheral blood mononuclear cells (PBMCs), CL blood perfusion b...

Exploring the Promise and Challenges of Artificial Intelligence in Biomedical Research and Clinical Practice.

Artificial intelligence (AI) is poised to revolutionize how science, and biomedical research in particular, are done. With AI, problem-solving and com...

Improving chimeric antigen receptor T-cell therapies by using artificial intelligence and internet of things technologies: A narrative review.

Cancer poses a formidable challenge in the field of medical science, prompting the exploration of innovative and efficient treatment strategies. One r...

Adaptable robots, ethics, and trust: a qualitative and philosophical exploration of the individual experience of trustworthy AI.

Much has been written about the need for trustworthy artificial intelligence (AI), but the underlying meaning of trust and trustworthiness can vary or...

Application of Artificial Intelligence in Tissue Engineering.

Tissue engineering, a crucial approach in medical research and clinical applications, aims to regenerate damaged organs. By combining stem cells, bioc...

Artificial Intelligence and Computational Biology in Gene Therapy: A Review.

One of the trending fields in almost all areas of science and technology is artificial intelligence. Computational biology and artificial intelligence...

Deep learning-based optimization of field geometry for total marrow irradiation delivered with volumetric modulated arc therapy.

BACKGROUND: Total marrow (lymphoid) irradiation (TMI/TMLI) is a radiotherapy treatment used to selectively target the bone marrow and lymph nodes in c...

Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research.

BACKGROUND: The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in p...

Supporting equitable and responsible highway safety improvement funding allocation strategies - Why AI prediction biases matter.

The existing methodologies for allocating highway safety improvement funding closely rely on the utilization of crash prediction models. Specifically,...