Transplantation

Robot-Assisted Stereotactic Microinjection Method for Precision Cell Transplantation in Rat and Canine Models.

Cell transplantation is a promising approach for addressing neurodegenerative conditions. In this study, we developed a robot-assisted stereotactic microinjection system for transplanting cells. We evaluated the factors that affect cellular graft viability and other properties, including the gauge of the syringe needle and the injection rate. We systematically compared the synchronous withdrawal i...

Effectiveness of Chatbot interventions for reducing caregiver burden: Protocol for a systematic review and meta-analysis.

This protocol outlines a systematic review and meta-analysis examining the effectiveness of fully automated, AI-driven chatbot interventions in reducing subjective burden among informal caregivers. We will search 8 electronic databases (PubMed, Web of Science, Embase, CINAHL, MEDLINE, Cochrane Library, PsycINFO, Scopus) and grey literature sources from January 2010 to December 2024 for randomized ...

Reduction of Acquisition Time in Fourier Transform Infrared Spectral Imaging by Deep Learning for Clinical Applications.

In infrared Fourier transform spectral imaging applied to biomedical challenges, data quality is of primary importance to achieving clinical objective...

Current Applications and Developments of Natural Language Processing in Kidney Transplantation: A Scoping Review.

BACKGROUND AND OBJECTIVE: Natural language processing (NLP) is a subfield of artificial intelligence that enables computers to process human language....

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, underpinning progress in regenerative medicine, cell ther...

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 radiomics feature-based SVR models with training ...

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 segmentation for pancreas and pancreatic cancer on...

AI-driven synthetic data generation for accelerating hepatology research: A study of the United Network for Organ Sharing (UNOS) database.

BACKGROUND AND AIMS: Clinical hepatology research often faces limited data availability, underrepresentation of minority groups, and complex data-shar...

Multiple omics-based machine learning reveals specific macrophage sub-clusters in renal ischemia-reperfusion injury and constructs predictive models for transplant outcomes.

BACKGROUND: Ischemia-reperfusion injury (IRI) is closely associated with numerous severe postoperative complications, including acute rejection, delay...

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 membrane bioreactor (MBR) treating high-salinity wast...

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 risks for individuals. Therefore, to evaluate the rang...

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 infection, leads to life-threatening organ dysfuncti...

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 breast cancer (TNBC) and human epidermal growth fa...

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 crossmatch compatibility by applying machine learning (ML)....

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 modifiable factors has been limited due to a lack of acc...

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 mass andsevere resorption in dental implant therapy....

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 transfusion. Deep machine learning surpasses trad...

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 mortality. We developed a recurrence prediction s...

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 microbial contamination detection during cell thera...

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 graft loss and poor patient prognosis, and it is impor...