Transplantation

Perception of AI Symptom Models in Oncology Nursing: Mixed Methods Evaluation Study.

BACKGROUND: Patients undergoing cancer treatment experience a significant symptom burden. The standard process of symptom management includes patient reporting and clinical response following symptom escalation. Emerging predictive symptom models use artificial intelligence (AI) components of machine learning and deep learning to identify the risk of symptom deterioration, facilitating earlier int...

The role of artificial intelligence in managing COVID-19 and long COVID: a narrative review.

The coronavirus disease 2019 (COVID-19) pandemic had an unprecedented global impact, resulting in both positive and negative consequences. The virus not only affected millions of lives worldwide but also caused long-term harm to multiple organ systems in many survivors, thereby substantially impairing quality of life. This persistent condition is now referred to as long COVID (LC). The aim of this...

Global emission factor dataset for Scope 3 machine learning applications.

The accurate and transparent estimation of greenhouse gas emissions is essential for corporate sustainability reporting and machine learning applicati...

Pahari POS-tagged corpus: A large-scale linguistic resource for NLP applications.

This paper presents the development of a Part-of-Speech (POS) tagged dataset for Pahari, an under-resourced Indo-Aryan language spoken in Azad Jammu a...

Comparison of large language models and conventional machine learning in postoperative outcome prediction: a retrospective, multi-national development and validation study.

BACKGROUND: Conventional machine learning (ML) models for predicting surgical outcomes have limitations in generalizability We explored large language...

Comprehensive Insight into Analytical Strategies for the Determination of Zolpidem and Its Metabolites in Different Matrices.

Zolpidem (ZLP), a non-benzodiazepine hypnotic of the imidazopyridine class, is widely prescribed for the short-term management of insomnia owing to it...

Deep Learning-Powered Scalable Cancer Organ Chip for Cancer Precision Medicine.

Functional precision oncology complements genomic approaches by directly testing treatment options on patient-derived models. However, existing platfo...

Predicting adverse events for risk stratification of chemotherapy based stem cell mobilization in multiple myeloma.

Autologous stem-cell transplantation is a fundamental therapy for multiple myeloma. Although inpatient chemo-based stem-cell mobilization (SCM) is sta...

Beyond the dose: a clearance-enabled in vitro platform for evaluating local therapies.

Inclusion of physiologically relevant clearance mechanisms into organ-on-a-chip models is essential to reproduce tissue exposure and predict therapeut...

Resolving sequential electron-proton transfer kinetics for electrochemical CO2 reduction at the Cu(100)/H2O interface via a quantum-classical framework.

Electron-transfer (ET) and proton-transfer (PT) events occurring at electrochemical interfaces ultimately dictate the efficiency of electrocatalytic e...

Powering the future: advances, challenges, and sustainability of polymer electrolytes in lithium-sulfur batteries.

Lithium-sulfur (Li-S) batteries offer a transformative theoretical energy density (∼2600 Wh kg-1), positioning them as strong candidates for next-gene...

Electrochemical NO-to-NH3 conversion on TM@NiN2 single-atom catalysts: a DFT and machine learning investigation.

Electrocatalytic reduction of nitrogen monoxide (NO) to ammonia (NH3) offers a win-win solution for environmental remediation and chemical production....

Which approach better samples extreme traffic conflicts? Conventional- vs. machine learning-based sampling methods.

Extreme value theory has been receiving much attention of late for proactively estimating crash risk through a two-step procedure that first samples e...

Development of Raman Spectroscopy and Machine Learning Methods for Protein Aggregate Quantification: Application to BSA in Chromatographic Processes.

Protein aggregation poses a significant risk to biopharmaceutical product quality, as even minor amounts of oligomeric species can compromise efficacy...

Legume Rotations and Conservation Tillage in Synergy: Yield Gains, Carbon Sequestration, and Climate Resilience.

Leguminous crop rotation (LC) and conservation tillage (CT) are nature-based solutions to mitigate climate change. Previous studies have shown signifi...

Halide Electrolytes for All-Solid-State Sodium Batteries: From Fundamental Chemistry to Interface Engineering.

All-solid-state sodium batteries (ASSSBs) stand out as a transformative energy storage technology, combining sodium's natural abundance with enhanced ...

Multiscale segmentation using hierarchical phase-contrast tomography and deep learning.

Biomedical systems span multiple spatial scales, encompassing tiny functional units to entire organs. Interpreting these systems through image segment...

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation.

BACKGROUND: Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, base...

Integrating network toxicology, machine learning, and molecular dynamics simulations to reveal tanshinone iia's dual mechanisms in TNBC and doxorubicin-induced cardiotoxicity.

Doxorubicin (Dox)-induced cardiotoxicity remains a critical barrier to optimizing breast cancer (BC) treatment, highlighting the urgent need to dissec...

Comprehensive tumour-immune profiling reveals TREM2+ tumour-associated macrophages facilitating lymph node metastasis in head and neck squamous cell carcinoma.

BACKGROUND: Lymph node (LN) metastasis is a well-established independent prognostic factor in head and neck squamous cell carcinoma (HNSCC). Formation...