Leukemia

Integrative analyses of 16S rDNA sequencing and serum metabolomics demonstrate significant roles for the oral microbiota and serum metabolites in post-kidney transplant diabetes mellitus.

Oral microbiota and serum metabolites play crucial roles in diabetes, but their relationship with po...

Computer-aided drug discovery of a dual-target inhibitor for ovarian cancer: therapeutic intervention targeting CDK1/TTK signaling pathway and structural insights in the NCI-60.

Ovarian cancer remains the third most prevalent and deadliest gynecologic malignancy worldwide, with...

A machine learning framework for cross-institute standardized analysis of flow cytometry in differentiating acute myeloid leukemia from non-neoplastic conditions.

Flow cytometry (FC) remains a cornerstone diagnostic tool for acute myeloid leukemia (AML), yet stan...

Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors.

PURPOSE: Noninvasive, accurate and novel approaches to predict patients who will achieve pathologica...

Radiomics-based machine learning in prediction of response to neoadjuvant chemotherapy in osteosarcoma: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Osteosarcoma (OS) is the most common primary bone malignancy, and neoadjuvant c...

Genome-wide association study revealed candidate genes associated with egg-laying time traits in layer chicken.

In modern intensive caged laying hen production, variations in egg-laying time (ELT) among layers of...

Cascade learning in multi-task encoder-decoder networks for concurrent bone segmentation and glenohumeral joint clinical assessment in shoulder CT scans.

Osteoarthritis is a degenerative condition that affects bones and cartilage, often leading to struct...

MACHINE LEARNING AND BIOINFORMATICS TO IDENTIFY COAGULATION BIOMARKERS IN SEPSIS-RELATED KIDNEY INJURY.

Background: Sepsis-associated acute kidney injury (SA-AKI) is a life-threatening complication with m...

A lightweight All-MLP time-frequency anomaly detection for IIoT time series.

Anomaly detection in the Industrial Internet of Things (IIoT) aims at identifying abnormal sensor si...

Identifying smart technology and artificial intelligence solutions for human factors and ergonomic challenges in all-hazard response: A survey study.

Emergency responders face significant human factors and ergonomic (HF/E) challenges related to physi...

CHRONIC CRITICAL ILLNESS IN BONE TRAUMA PATIENTS: AN AI-BASED APPROACH FOR INTENSIVE CARE UNIT HEALTHCARE PROVIDERS.

Background: Chronic critical illness (CCI) is a serious condition characterized by a prolonged cours...

Use of machine learning techniques to predict poor survival after hematopoietic cell transplantation for myelofibrosis.

With the incorporation of effective therapies for myelofibrosis (MF), accurately predicting outcomes...

Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes.

Inflammation is increasingly recognized as a critical factor in acute myeloid leukemia (AML) pathoge...

Quantitative and qualitative metrics of tumor stroma in predicting ovarian cancer outcomes and expansion of its study with AI-based tools.

Epithelial ovarian cancer remains one of the deadliest gynecologic malignancies, with late-stage dia...

Prediction of bacterial and fungal bloodstream infections using machine learning in patients undergoing chemotherapy.

PURPOSE: This study aimed to develop a machine learning (ML) model to predict bloodstream infection ...

Nanotechnology-Enhanced siRNA Delivery: Revolutionizing Cancer Therapy.

RNA interference (RNAi) has emerged as a transformative approach for cancer therapy, enabling precis...

Segment-Weighting Similarity-Based Fragment-Learning Model for Single-Cell Raman Spectral Analysis.

Raman spectroscopy provides intrinsic biochemical profiles of all cellular biomolecules in a segment...

An approach to screen susceptible rats and efficacy of an antidepressive treatment after chronic stress.

Chronic stress during life has been considered a risk factor for the development of psychiatric illn...

Not all clinical data in the United States are fragmented.

When One Size Does not Fit All-Artificial Intelligence in Australian Rural Health.

AIMS: Artificial intelligence (AI) is having an increasing impact on many aspects of our day-to-day ...

A Combined-Mode Machine Learning Model for Predicting Stroke Recurrence During Hospitalization in Patients with Acute Minor Ischemic Stroke.

Acute minor ischemic stroke patients often experience recurrence shortly after symptom onset, highli...