Public Health & Policy

Stem Cell Research

Latest AI and machine learning research in stem cell research for healthcare professionals.

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Radiation-induced acoustic signal denoising using a supervised deep learning framework for imaging and therapy monitoring.

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing the invisible radia...

Quantitative Modeling of Stemness in Single-Cell RNA Sequencing Data: A Nonlinear One-Class Support Vector Machine Method.

Intratumoral heterogeneity and the presence of cancer stem cells are challenging issues in cancer th...

Advances in volumetric bioprinting.

The three-dimensional (3D) bioprinting technologies are suitable for biomedical applications owing t...

Legal and ethical principles governing the use of artificial intelligence in radiology services in South Africa.

Artificial intelligence (AI) will drastically change the healthcare system. Radiology is one special...

Should AI allocate livers for transplant? Public attitudes and ethical considerations.

BACKGROUND: Allocation of scarce organs for transplantation is ethically challenging. Artificial int...

Broadening the horizon: potential applications of CAR-T cells beyond current indications.

Engineering immune cells to treat hematological malignancies has been a major focus of research sinc...

Clinical and Dosimetric Impact of 2D kV Motion Monitoring and Intervention in Liver Stereotactic Body Radiation Therapy.

PURPOSE: Positional errors resulting from motion are a principal challenge across all disease sites ...

[Multistain deep learning as a prognostic and predictive biomarker in colorectal cancer].

The tumor immune microenvironment (TIME) plays a crucial prognostic and predictive role in solid mal...

Responsible (use of) AI.

Although there is a rich history of philosophical definitions of ethics when applied to human behavi...

Artificial Intelligence Aided Ethics in Frontier Research.

Emergent technologies are frequently demonized due to the fear of the unknown. The doubts and alarms...

Diabetes and artificial intelligence beyond the closed loop: a review of the landscape, promise and challenges.

The discourse amongst diabetes specialists and academics regarding technology and artificial intelli...

Using expert-reviewed CSAM to train CNNs and its anthropological analysis.

Machine learning methods for the identification of child sexual abuse materials (CSAM) have been pre...

Accurate staging of chick embryonic tissues via deep learning of salient features.

Recent work shows that the developmental potential of progenitor cells in the HH10 chick brain chang...

Guiding principles and proposed classification system for the responsible adoption of artificial intelligence in scientific writing in medicine.

The integration of large language models (LLMs) and artificial intelligence (AI) into scientific wri...

Breaking the unvirtuous cycle: barriers and opportunities for research and development in Paraguay. A case study.

INTRODUCTION: Medical research and development (R&D) is an undoubtedly relevant activity to drive in...

On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers.

An ensemble of classifiers combines several single classifiers to deliver a final prediction or clas...

Feasibility of Monte Carlo dropout-based uncertainty maps to evaluate deep learning-based synthetic CTs for adaptive proton therapy.

BACKGROUND: Deep learning has shown promising results to generate MRI-based synthetic CTs and to ena...

A Weakly Supervised Learning Method for Cell Detection and Tracking Using Incomplete Initial Annotations.

The automatic detection of cells in microscopy image sequences is a significant task in biomedical r...

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