Leukemia

Admission-Based Machine-Learning Models for Predicting Mechanical Ventilation and Mortality in Fibrotic Interstitial Lung Disease: A Multicenter Cohort Study with External Validation.

BACKGROUND: Admission-based risk stratification tools are limited for hospitalized patients with fibrotic interstitial lung disease (F-ILD). AIMS: To develop and externally validate admission-based machine-learning models for predicting mechanical ventilation (MV), 30-day and 3-month mortality, and long-term all-cause and cause-specific mortality in hospitalized patients with F-ILD. STUDY DESIGN: ...

ChemoCardioNet: An Explainable Multimodal Transformer for Early Prediction of Chemotherapy-Induced Cardiotoxicity.

Chemotherapy-induced cardiotoxicity (CIC) remains a major cause of morbidity and mortality among cancer survivors, and conventional monitoring often fails to detect early subclinical cardiac injury. We propose ChemoCardioNet, an explainable multimodal deep learning framework that predicts cardiotoxicity risk before clinical manifestation by integrating electrocardiograms (ECG), echocardiography, c...

Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer using a Longitudinal US-based Stack-model.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of a longitudinal ultrasound (US)-based stack-model for early prediction of pathologi...

BanglaRiceLeaf: A benchmark dataset for automated rice leaf disease detection and health classification in Bangladesh.

Rice leaf diseases pose a major challenge to crop health and agricultural productivity, particularly when timely and accurate diagnosis is required un...

AI In Leukemia Diagnostics: Complementing the Pathologist's Role.

Artificial intelligence (AI) is reshaping every stage of leukemia diagnostics, from digital morphology and multiparameter flow cytometry to next-gener...

Unraveling the adverse outcome pathways of metabolic dysfunction-associated steatotic liver disease triggered by environmental mixtures via biological knowledge-driven machine learning.

Environmental pollutant mixtures are potential risk factors for metabolic dysfunction-associated steatotic liver disease (MASLD), yet their joint effe...

ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell ...

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers, with survival rates influenced by a variety of factors, including earl...

Machine Learning-based Prediction of Unplanned Acute Care in Outpatients Receiving S-1 Chemotherapy.

BACKGROUND/AIM: The increasing use of oral anticancer agents in outpatient settings has led to a growing need for unplanned acute care (UAC) due to tr...

Machine learning-based prediction of ICU admission and mortality in Crimean-Congo hemorrhagic fever by using wide-range targeted metabolomics.

PURPOSE: This study aimed to evaluate the potential of amino-acid profiles to predict disease progression in patients with Crimean-Congo Hemorrhagic F...

Radiomics-based causal machine learning for exploratory treatment-effect estimation of neoadjuvant chemotherapy cycle intensity in osteosarcoma: a proof-of-concept study.

BACKGROUND: Radiomics-based modeling has shown promise for characterizing tumor heterogeneity, but its integration with causal machine learning for tr...

Trajectory analysis of sleep disorders and anxiety-depression in female breast cancer patients undergoing chemotherapy: based on group-based Multi-Trajectory Model and machine learning.

BACKGROUND: Sleep disorders and anxiety-depression symptoms can significantly impair the quality of life and treatment adherence among breast cancer p...

Machine learning reveals X chromosome transcriptional signatures that classify systemic lupus erythematosus in females.

BACKGROUND: Systemic lupus erythematosus (SLE) has a significant female bias; however, it remains unclear whether X-chromosomal dysregulation increase...

Selective Effects of Backbone Cyclization and Disulfide Bonding as Global Covalent Constraints on the Conformational Ensemble of Sunflower Trypsin Inhibitor-1.

Backbone cyclization and disulfide bonding are key global covalent constraints in many bioactive peptides, yet their individual and combined effects o...

Quality Evaluation of Large Language Model-Assisted Generation of Initial Senior Physician Ward Round Records for Patients With Acute Poisoning: Cross-Sectional Study.

BACKGROUND: Large language models (LLMs) have shown potential in medical text generation. Senior physician ward round records are critical documents w...

Noninvasive and minimally invasive approaches for acute and chronic stress assessment in dairy cattle.

In modern dairy production, cattle are routinely exposed to a wide range of management-related, environmental, and biological stressors all of which c...

Integrating Machine Learning and Single-Cell Analysis to Reveal the Diagnostic and Therapeutic Value of Regulated Cell Death Mechanisms in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) treatment faces significant challenges, particularly in tumor growth, metastasis, and drug resistance. While several pr...

[Value of a deep learning-based visual model for predicting postoperative upper limb functional recovery after severe acute cervical spinal cord injury].

Objective: To assess the value of a deep learning-based visual model for predicting postoperative upper limb functional recovery after severe acute ce...

OracleScreen-LILRB4: machine learning-guided discovery of myeloid immune checkpoint binders validated in patient-derived cells.

The identification of small molecule modulators of immune checkpoint proteins remains a significant challenge in drug discovery due to the flat, featu...

Explainable machine learning identifies small high-performance gene signatures from full transcriptomes in human liver preservation cohorts.

Transcriptomic studies of liver preservation and ischemia-reperfusion injury (IRI) often report large gene lists that are difficult to translate into ...