Transplantation

Re-imagining human cell culture media: Challenges, innovations, and future directions.

The development of optimized culture media is pivotal to advancements in human cell culture, underpi...

Estimating patient-specific organ doses from head and abdominal CT scans via machine learning with optimized regulation strength and feature quantity.

PURPOSE: This study aims to investigate estimation of patient-specific organ doses from CT scans via...

A snapshot of challenges and opportunities faced by the scientific workforce in liver transplantation-a survey of the International Liver Transplantation Society (ILTS).

Basic and translational research (B&TR) in liver transplantation (LT) underwent considerable change...

Structured hashing with deep learning for modality, organ, and disease content sensitive medical image retrieval.

Evidence-based medicine is the preferred procedure among clinicians for treating patients. Content-b...

Processing Mobility Data Through Artificial Intelligence Can Identify Patterns of Physical Activity in Liver Transplant Candidates.

Segment Like A Doctor: Learning reliable clinical thinking and experience for pancreas and pancreatic cancer segmentation.

Pancreatic cancer is a lethal invasive tumor with one of the worst prognosis. Accurate and reliable ...

Light spectrum mediated improved graft-healing response by enhanced expression of transport protein in vegetables under drought conditions.

Vegetable production faces unprecedented challenges due to a rapid change in climate. Among several ...

Enhanced nitrogen prediction and mechanistic process analysis in high-salinity wastewater treatment using interpretable machine learning approach.

This study introduces an interpretable machine learning framework to predict nitrogen removal in mem...

A sentiment analysis of YouTube videos from donor-conceived people, utilizing artificial intelligence (ChatGPT).

RESEARCH QUESTION: What is the tone of donor-conceived people (DCP) towards their donor-conceived st...

Introduction of a hybrid approach based on statistical shape model and Adaptive Neural Fuzzy Inference System (ANFIS) to assess dosimetry uncertainty: A Monte Carlo study.

The increasing use of ionizing radiation has raised concerns about adverse and long-term health risk...

Comprehensive integration of diagnostic biomarker analysis and immune cell infiltration features in sepsis via machine learning and bioinformatics techniques.

INTRODUCTION: Sepsis, a critical medical condition resulting from an irregular immune response to in...

Transcriptome analysis reveals the potential role of neural factor EN1 for long-terms survival in estrogen receptor-independent breast cancer.

Breast cancer patients with estrogen receptor-negative (ERneg) status, encompassing triple negative ...

Machine learning enhanced immunologic risk assessments for solid organ transplantation.

The purpose of this study was to enhance the prediction of solid-organ recipient and donor crossmatc...

Development of a natural language processing algorithm to extract social determinants of health from clinician notes.

Disparities in access to the organ transplant waitlist are well-documented, but research into modifi...

Automatic Segmentation of Bone Graft in Maxillary Sinus via Distance Constrained Network Guided by Prior Anatomical Knowledge.

Maxillary Sinus Lifting is a crucial surgical procedure for addressing insufficient alveolar bone ma...

Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study.

Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to...

Cold storage surpasses the impact of biological age and donor characteristics on red blood cell morphology classified by deep machine learning.

Assessment of the morphology of red blood cells (RBCs) can improve clinical benefits following blood...

Machine learning aided UV absorbance spectroscopy for microbial contamination in cell therapy products.

We demonstrate the feasibility of machine-learning aided UV absorbance spectroscopy for in-process m...

Identification of ALDH2 as a novel target for the treatment of acute kidney injury in kidney transplantation based on WGCNA and machine learning algorithms and exploration of its potential mechanism of action using animal experiments.

BACKGROUND: Acute kidney injury (AKI) after kidney transplantation is one of the main causes of graf...

Enhancing DILI toxicity prediction through integrated graph attention (GATNN) and dense neural networks (DNN).

Drug-induced liver injury (DILI) toxicity is a condition when drugs have a destructive effect on the...

Artificial intelligence quantification and experienced reader computed tomography analysis for differentiating normal from minimally and mildly diseased coronary arteries: an early real-world compatibility study.

Differentiating normal from minimally and mildly diseased coronary arteries on coronary computed tom...