Stem Cell Research

Use of machine learning models to identify National Institutes of Health-funded cardiac arrest research.

OBJECTIVE: To compare the performance of three artificial intelligence (AI) classification strategie...

Should we express gratitude in human-AI interaction: The online public's moral stance toward artificial intelligence assistants in China.

The ethical dimensions of human-AI (artificial intelligence) interaction demand attention. As artifi...

Perioperative goal-directed therapy with artificial intelligence to reduce the incidence of intraoperative hypotension and renal failure in patients undergoing lung surgery: A pilot study.

STUDY OBJECTIVE: The aim of this study was to investigate whether goal-directed treatment using arti...

An interpretable ensemble model combining handcrafted radiomics and deep learning for predicting the overall survival of hepatocellular carcinoma patients after stereotactic body radiation therapy.

PURPOSE: Hepatocellular carcinoma (HCC) remains a global health concern, marked by increasing incide...

A multicentre implementation trial of an Artificial Intelligence-driven biomarker to inform Shared decisions for androgen deprivation therapy in men undergoing prostate radiotherapy: the ASTuTE protocol.

BACKGROUND: Androgen deprivation therapy (ADT) improves outcomes in men undergoing definitive radiot...

Machine learning models for prognosis prediction in regenerative endodontic procedures.

BACKGROUND: This study aimed to establish and validate machine learning (ML) models to predict the p...

Predicting low density lipoprotein cholesterol target attainment using machine learning in patients with coronary artery disease receiving moderate-dose statin therapy.

Low-density lipoprotein cholesterol (LDL-C) is an important factor in the development of cardiovascu...

X-scPAE: An explainable deep learning model for embryonic lineage allocation prediction based on single-cell transcriptomics revealing key genes in embryonic cell development.

In single-cell transcriptomics research, accurately predicting cell lineage allocation and identifyi...

Real-time adaptive proton therapy: An AI-based spatio-temporal mono-energetic dose calculation model (CC-LSTM).

PURPOSE: To develop a fully AI-based dose estimation model capable of learning and estimating single...

Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study.

BACKGROUND: According to meta-analyses of randomised controlled trials (RCTs), therapist-guided inte...

Importance of dataset design in developing robust U-Net models for label-free cell morphology evaluation.

Advances in regenerative medicine highlighted the need for label-free cell image analysis to replace...

AI Ethics beyond Principles: Strengthening the Life-world Perspective.

The search for ethical guidance in the development of artificial intelligence (AI) systems, especial...

EEG Temporal-Spatial Feature Learning for Automated Selection of Stimulus Parameters in Electroconvulsive Therapy.

The risk of adverse effects in Electroconvulsive Therapy (ECT), such as cognitive impairment, can be...

Using Facial Skin Artificial Intelligence (AI) to Capture Atopic Dermatitis Patients' Response to Therapy: A Single-Center Prospective Study.

Assessing multiple MRI sequences in deep learning-based synthetic CT generation for MR-only radiation therapy of head and neck cancers.

PURPOSE: This study investigated the effect of multiple magnetic resonance (MR) sequences on the qua...

Patient performance assessment methods for upper extremity rehabilitation in assist-as-needed therapy strategies: a comprehensive review.

This paper aims to comprehensively review patient performance assessment (PPA) methods used in assis...

Revolutionizing prostate cancer therapy: Artificial intelligence - Based nanocarriers for precision diagnosis and treatment.

Prostate cancer is one of the major health challenges in the world and needs novel therapeutic appro...

Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema.

Diabetic Macular Edema (DME) is a major complication of diabetic retinopathy characterized by fluid ...

A comparison of different machine learning classifiers in predicting xerostomia and sticky saliva due to head and neck radiotherapy using a multi-objective, multimodal radiomics model.

. Although radiotherapy techniques are a primary treatment for head and neck cancer (HNC), they are ...

AI-based medical ethics education: examining the potential of large language models as a tool for virtue cultivation.

BACKGROUND: With artificial intelligence (AI) increasingly revolutionising medicine, this study crit...

Machine learning-based screening and molecular simulations for discovering novel PARP-1 inhibitors targeting DNA repair mechanisms for breast cancer therapy.

Cancer remains one of the leading causes of death worldwide, with the rising incidence of breast can...