Transplantation

Towards the theory for mitigating gradient issues and dead neurons in deep learning through a modified Gaussian activation function.

Activation functions are essential in deep learning optimization for introducing non-linearity, shaping gradient dynamics, and influencing weight initialization. This paper presents a modified Gaussian function called R-Gaussian, an activation function that dynamically adapts to pre-activation values, ensuring stable gradient propagation. Unlike trainable activation functions, R-Gaussian derives i...

Deciphering the role of angiogenesis in glioblastoma: Integrative insights from transcriptomic profiling, single-cell sequencing and interpretable machine learning approaches.

Glioblastoma (GBM), a highly vascularized and aggressive primary brain tumor, presents unresolved questions regarding the functional significance of angiogenesis-related genes (ARGs) in disease progression. To systematically investigate this, we employed univariate Cox regression followed by LASSO regression analysis to identify prognosis-associated ARGs. These candidates were subsequently evaluat...

Explainable machine learning-based prediction of psoriatic arthritis flares using heterogenous real-world data for personalised patient care.

Psoriatic arthritis (PsA) is a chronic inflammatory disease characterised by unpredictable flare-ups that are difficult to forecast, particularly in p...

PL-Seg: Partially labeled abdominal organ segmentation via classwise orthogonal contrastive learning and progressive self-distillation.

Accurate segmentation of abdominal organs in Computed Tomography (CT) scans is crucial for effective lesion diagnosis, radiotherapy planning, and pati...

Novel machine learning framework for multidimensional biological age estimation reveals heterogeneous aging of organ systems.

OBJECTIVE: Existing biological age (BA) models often oversimplify aging's complexity, offering single-dimensional metrics. However, these fail to capt...

Review on electrochemical sensors for anticancer drug susceptibility testing.

Anticancer drug susceptibility tests play an essential role in areas such as drug development, pharmacokinetic research, and precision oncology. Acros...

Integrated multi-omics analyses identified the H3K18la-based spatiotemporal characteristics and risk-stratified treatment strategy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer, characterized by high mortality, recurrence, and metastasis. Despite a...

Abdominal multi-organ segmentation on 3D negative-contrast CT cholangiopancreatography: a comparative study of deep learning methods.

OBJECTIVES: This study aims to automate segmentation of the biliary and pancreatic systems on 3D negative-contrast CT cholangiopancreatography (3D-nCT...

Total-body [18F]FDG-PET/CT imaging of healthy volunteers with minimal effective dose.

PURPOSE: High-sensitivity, total-body (TB) positron emission tomography (PET) and computed tomography (CT) imaging systems enable substantial reductio...

AI-Driven Recipient Recognition System for Corneal Transplantation.

PURPOSE: The objective of this study is to enhance the efficiency and expediency of the corneal recipient selection process from extensive recipient l...

Deep learning for automated alveolar cleft segmentation and bone graft volume estimation in cone-beam computed tomography imaging: a multicenter study.

OBJECTIVE: To train and validate a deep learning-based diagnostic tool capable of accurately segmenting the alveolar cleft region and automatically es...

Deep learning and molecular dynamics reveal promising EZH2 inhibitors for epigenetic cancer targeting.

Fine-tuned REINVENT generative model integrated with structure- and ligand-based computational approaches was applied to identify novel EZH2 inhibitor...

Responsible Use of Artificial Intelligence to Improve Kidney Care: A Statement from the American Society of Nephrology.

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive analytics, machine learning, deep learning, and ge...

Mapping systemic inter-organ metabolic networks across glycemic continuum using whole-body [18F]FDG PET/CT and machine learning.

PURPOSE: Glucose homeostasis relies on coordinated interactions among multiple organs, and its disruption relates to diabetes development. This study ...

Identification of lymphangiogenesis-related diagnostic model for predicting abdominal aortic aneurysm onset and progression and validation of lymphopoiesis in abdominal aortic aneurysm.

This study aims to explore the lymphangiogenesis (LG)-related diagnostic markers of abdominal aortic aneurysm (AAA) through bioinformatics, as well as...

An Interpretable Machine Learning Model for Early Multitemporal Prediction of Onset of Acute Kidney Injury in Intensive Care Unit Patients with Severe Trauma.

Background: Acute Kidney Injury (AKI), a leading organ failure cause in critical patients, demands early high-risk identification to enhance outcomes....

CSF1R and macrophage infiltration: Integrated magnetic resonance imaging radiomics and deep learning-driven models for the preoperative assessment of glioma.

BACKGROUND: Colony-stimulating factor-1 receptor (CSF1R) signaling is crucial for the ability of tumor-associated macrophages (TAMs) to establish an i...

Perioperative Extracorporeal Membrane Oxygenation Use in Lung Transplantation: Analysis of Outcomes and Future Directions.

Extracorporeal membrane oxygenation (ECMO) has emerged as a critical intervention in the management of patients with end-stage lung disease undergoing...

Virus-like particles as versatile scaffolds for nanobiosensors and nanoreactors: Design, applications, and future perspectives.

Virus-like particles (VLPs) have emerged as highly versatile and programmable nanoscaffolds for the development of advanced biodevices, particularly i...

Biased minds, sensitive hearts: Divergent neural signatures of interpersonal sensitivity in atypical and non-atypical depression.

BACKGROUND: Atypical depression (AD) is a distinct subtype of depression, with interpersonal sensitivity as one of its core characteristics. However, ...