Transplantation

Dental Artificial Intelligence Systems: A Review of Various Data Types.

With the rapid development of dental artificial intelligence systems (DAIS), a new field known as "Data Dentistry", proposed by Schwendicke in 2021, has successfully bridged the gap between medicine and engineering. This literature review introduces advanced techniques in data collection, outlines the current state of DAIS in data processing, and anticipates the future of DAIS by emphasizing the i...

Deep Learning-Based 3D Single-Cell Imaging Analysis Pipeline Enables Quantification of Cell-Cell Interaction Dynamics in the Tumor Microenvironment.

UNLABELLED: The three-dimensional (3D) tumor microenvironment (TME) comprises multiple interacting cell types that critically impact tumor pathology and therapeutic response. Efficient 3D imaging assays and analysis tools could facilitate profiling and quantifying distinctive cell-cell interaction dynamics in the TMEs of a wide spectrum of human cancers. Here, we developed a 3D live-cell imaging a...

Deep Learning-based Fibrosis Extent on Computed Tomography Predicts Outcome of Fibrosing Interstitial Lung Disease Independent of Visually Assessed Computed Tomography Pattern.

Radiologic pattern has been shown to predict survival in patients with fibrosing interstitial lung disease. The additional prognostic value of fibros...

Development of a pharmaceutical science systematic review process using a semi-automated machine learning tool: Intravenous drug compatibility in the neonatal intensive care setting.

Our objective was to establish and test a machine learning-based screening process that would be applicable to systematic reviews in pharmaceutical sc...

Proposal of a standardized training curriculum for open and robot-assisted kidney transplantation.

Standardized training programs for open (OKT) and robot-assisted kidney transplantation (RAKT) remain unmet clinical needs. To fill this gap, we desig...

Protein sequence design on given backbones with deep learning.

Deep learning methods for protein sequence design focus on modeling and sampling the many- dimensional distribution of amino acid sequences conditione...

Deep learning-based radiomics allows for a more accurate assessment of sarcopenia as a prognostic factor in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common malignancies and is a major cause of cancer-related mortalities worldwide (Forner et al., 201...

The AI Agent in the Room: Informing Objective Decision Making at the Transplant Selection Committee

Transplantation is one of the few areas in medicine where the definitive treatment is rationed. Subjective decision-making pose challenges towards the...

Clinical Information Extraction with Large Language Models: A Case Study on Organ Procurement.

Recent work has demonstrated that large language models (LLMs) are powerful tools for clinical information extraction from unstructured text. However,...

Derivation and Experimental Performance of Standard and Novel Uncertainty Calibration Techniques.

To aid in the transparency of state-of-the-art machine learning models, there has been considerable research performed in uncertainty quantification (...

Modeling Precision Feedback Knowledge for Healthcare Professional Learning and Quality Improvement.

Healthcare providers learn continuously, but better support for provider learning is needed as new biomedical knowledge is produced at an increasing r...

An effective deep learning-based approach for splice site identification in gene expression.

A crucial stage in eukaryote gene expression involves mRNA splicing by a protein assembly known as the spliceosome. This step significantly contribute...

The changes in bladder function and symptoms after robot-assisted sacrocolpopexy and transvaginal mesh surgery for pelvic organ prolapse.

OBJECTIVE: This study is aimed to compare the impact on bladder function and symptoms between robotic sacrocolpopexy (RSC) and transvaginal mesh surge...

Deep Learning-Assisted Analysis of Immunopeptidomics Data.

Liquid chromatography-coupled mass spectrometry (LC-MS/MS) is the primary method to obtain direct evidence for the presentation of disease- or patient...

3D-Bioprinting and AI-empowered Anatomical Structure Designing: A Review.

BACKGROUND: The recent advancements and detailed studies in the field of 3D bioprinting have made it a promising avenue in the field of organ shortage...

Predicting patient-specific organ doses from thoracic CT examinations using support vector regression algorithm.

PURPOSE: This study aims to propose and develop a fast, accurate, and robust prediction method of patient-specific organ doses from CT examinations us...

Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.

Cell tracking is an essential step in extracting cellular signals from moving cells, which is vital for understanding the mechanisms underlying variou...

Deep Learning-Based HLA Allele Imputation Applicable to GWAS.

Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA ...

DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.

Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformati...

Prediction of early-phase cytomegalovirus pneumonia in post-stem cell transplantation using a deep learning model.

BACKGROUND: Diagnostic challenges exist for CMV pneumonia in post-hematopoietic stem cell transplantation (post-HSCT) patients, despite early-phase ra...