Transplantation

Using ChatGPT for Kidney Transplantation: Perceived Information Quality by Race and Education Levels.

BACKGROUND: Kidney transplantation is a complex process requiring extensive preparation and ongoing monitoring. Artificial intelligence (AI)-powered chatbots hold potential for providing accessible health information, but our understanding of their role in offering health advice for kidney transplantation and how individuals assess such advice remains limited. This study investigates how individua...

Multicenter integration analysis of TRP channels revealed potential mechanisms of immunosuppressive microenvironment activation and identified a machine learning-derived signature for improving outcomes in gliomas.

AIM: This study aimed to explore the mechanisms of transient receptor potential (TRP) channels on the immune microenvironment and develop a TRP-related signature for predicting prognosis, immunotherapy response, and drug sensitivity in gliomas.

Artificial intelligence for forecasting live donor kidney function.

Predicting Donor Selection and Multi-Organ Transplantation within Organ Procurement Organizations Using Machine Learning.

Organ procurement organizations (OPOs) play a crucial role in the field of organ transplantation, serving as key intermediaries in the process of orga...

C2P-GCN: Cell-to-Patch Graph Convolutional Network for Colorectal Cancer Grading.

Graph-based learning approaches, due to their ability to encode tissue/organ structure information, are increasingly favored for grading colorectal ca...

Visualization of Surgical Needle Tips Hidden Inside Organs Using Generative Adversarial Networks.

Postoperative complications in surgery are particularly prevalent in laparoscopic procedures, which are difficult for physicians to perform. One compl...

Optimization of Autonomous Driving Image Detection Based on RFAConv and Triplet Attention

YOLOv8 plays a crucial role in the realm of autonomous driving, owing to its high-speed target detection, precise identification and positioning, an...

ConnectVR: A Trigger-Action Interface for Creating Agent-based Interactive VR Stories

The demand for interactive narratives is growing with increasing popularity of VR and video gaming. This presents an opportunity to create interacti...

LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation

As the demand for more personalized recommendation grows and a dramatic boom in commercial scenarios arises, the study on multi-scenario recommendat...

Design optimization of geometrically confined cardiac organoids enabled by machine learning techniques.

Stem cell organoids are powerful models for studying organ development, disease modeling, drug screening, and regenerative medicine applications. The ...

An Effective Software Risk Prediction Management Analysis of Data Using Machine Learning and Data Mining Method

For one to guarantee higher-quality software development processes, risk management is essential. Furthermore, risks are those that could negatively...

Quantification of follicles in human ovarian tissue using image processing software and trained artificial intelligence†.

Cancer survival rates in prepubertal girls and young women have risen in recent decades due to increasingly efficient treatments. However, many such t...

Embedding-based Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes

Cancer clinics capture disease data at various scales, from genetic to organ level. Current bioinformatic methods struggle to handle the heterogeneo...

Dynamic Online Recommendation for Two-Sided Market with Bayesian Incentive Compatibility

Recommender systems play a crucial role in internet economies by connecting users with relevant products or services. However, designing effective r...

Advancing drug-response prediction using multi-modal and -omics machine learning integration (MOMLIN): a case study on breast cancer clinical data.

The inherent heterogeneity of cancer contributes to highly variable responses to any anticancer treatments. This underscores the need to first identif...

HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen p...

Prediction of immunochemotherapy response for diffuse large B-cell lymphoma using artificial intelligence digital pathology.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous and prevalent subtype of aggressive non-Hodgkin lymphoma that poses diagnostic and prognostic...

[Development of green pesticides from traditional Chinese medicines based on artificial intelligence and compatibility of traditional Chinese medicines].

The food security of China as a big agricultural country is attracting increasing attention. With the progress in the traditional Chinese medicine ind...

Patient-Reported Outcomes for Robot-Assisted Laparoscopic Extravascular Renal Vein Stent Placements for Nutcracker Syndrome.

Nutcracker phenomenon is the compression of the left renal vein between the superior mesenteric artery (SMA) and the abdominal aorta. Nutcracker synd...

Transplant nephropathology: Wherefrom, wherein, and whereto.

Renal pathology is a relatively recent entry in nephrology. While diseases of the kidney are old, their study began in the 19th century with the repor...