Stem Cell Research

Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.

Mathematical modelling has proven to be a valuable tool in predicting the delivery and efficacy of molecular, antibody-based, nano and cellular therapy in solid tumours. Mathematical models based on our understanding of the biological processes at subcellular, cellular and tissue level are known as mechanistic models that, in turn, are divided into continuous and discrete models. Continuous models...

[Validation of a decision tree for selective dry cow therapy of dairy for a digital expert system].

In this study, a decision tree derived from scientific literature on selective dry cow therapy (ST), which was developed as a knowledge base for a digital expert system, was evaluated. The decision tree merges algorithmic (based on cell count results) and cultural (based on milk sample findings) approaches.During a two-year project period (August 2021-September 2023), ST was carried out on 19 dair...

Predicting cell properties with AI from 3D imaging flow cytometer data.

Predicting the properties of tissues or organisms from the genomics data is widely accepted by the medical community. Here we ask a question: can we p...

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 strategies against manually classified National Institutes ...

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 prognosis of regenerative endodontic procedures (RE...

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 identifying differences between lineages are crucial for un...

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 conventional microscopic observation for non-inva...

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

The search for ethical guidance in the development of artificial intelligence (AI) systems, especially in healthcare and decision support, remains a c...

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 assist-as-needed (AAN) robotic therapy for upper extrem...

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 approaches to overcome the limitations of conventional ...

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 accumulation in the macula, leading to vision impa...

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 still associated with substantial toxicity and sid...

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 critically evaluates the integration of large language...

Exploring ethical considerations in medical research: Harnessing pre-generated transformers for AI-powered ethics discussions.

INTRODUCTION: In medical research involving human subjects, ethical review is essential to protect individuals. However, concerns have been raised abo...

Design and optimization of tamarind seed polysaccharide-based scaffold for tissue engineering applications using statistical modeling and machine learning, and it's in-vitro validation.

This study explores the development and optimization of a novel biomaterial scaffold for tissue engineering, composed of Tamarind seed polysaccharide ...

Enhancing neural stem cell integration in the injured spinal cord through targeted PTEN modulation.

JOURNAL/nrgr/04.03/01300535-202604000-00039/figure1/v/2025-06-30T060627Z/r/image-tiff Spinal cord injury results in permanent loss of neurological fun...

Marigold: a machine learning-based web app for zebrafish pose tracking.

BACKGROUND: High-throughput behavioral analysis is important for drug discovery, toxicological studies, and the modeling of neurological disorders suc...

Comparative efficacy of robot-assisted therapy associated with other different interventions on upper limb rehabilitation after stroke: A protocol for a network meta-analysis.

INTRODUCTION: Post-stroke movement disorders are common, especially upper limb dysfunction, which seriously affects the physical and mental health of ...

Machine learning and molecular subtyping reveal the impact of diverse patterns of cell death on the prognosis and treatment of hepatocellular carcinoma.

Programmed cell death (PCD) is a significant factor in the progression of hepatocellular carcinoma (HCC) and might serve as a crucial marker for predi...

Semiautomated Extraction of Research Topics and Trends From National Cancer Institute Funding in Radiological Sciences From 2000 to 2020.

PURPOSE: Investigators and funding organizations desire knowledge on topics and trends in publicly funded research but current efforts for manual cate...