Leukemia

Cytogenetics and genomics in pediatric acute lymphoblastic leukaemia.

The last five decades have witnessed significant improvement in diagnostics, treatment and managemen...

FGFR1Pred: an artificial intelligence-based model for predicting fibroblast growth factor receptor 1 inhibitor.

Fibroblast growth factor receptors (FGFRs) are a family of cell surface receptors that bind to fibro...

Deep learning for the prediction of the chemotherapy response of metastatic colorectal cancer: comparing and combining H&E staining histopathology and infrared spectral histopathology.

Colorectal cancer is a global public health problem with one of the highest death rates. It is the s...

Generalizability of prostate MRI deep learning: does one size fit all data?

An appraisal of the performance of AI tools for chronic stroke lesion segmentation.

Automated demarcation of stoke lesions from monospectral magnetic resonance imaging scans is extreme...

Childhood Leukemia Classification via Information Bottleneck Enhanced Hierarchical Multi-Instance Learning.

Leukemia classification relies on a detailed cytomorphological examination of Bone Marrow (BM) smear...

Class-imbalanced complementary-label learning via weighted loss.

Complementary-label learning (CLL) is widely used in weakly supervised classification, but it faces ...

Post-chemotherapy robot-assisted retroperitoneal lymph node dissection for metastatic germ cell tumors: safety and perioperative outcomes.

PURPOSE: To evaluate the feasibility, safety, and early oncologic outcomes after post-chemotherapy r...

Survey shows all surgical residents have exposure to robotic surgery yet no formalized curricula exist amongst programs: A Southwest Surgical Congress Survey.

BACKGROUND: Increased robotic surgery exposure during general surgery training occurs at many instit...

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus...

Artificial intelligence-based radiomics in bone tumors: Technical advances and clinical application.

Radiomics is the extraction of predefined mathematic features from medical images for predicting var...

A Benchmark Study of Graph Models for Molecular Acute Toxicity Prediction.

With the wide usage of organic compounds, the assessment of their acute toxicity has drawn great att...

Validation of bone mineral density measurement using quantitative CBCT image based on deep learning.

The bone mineral density (BMD) measurement is a direct method of estimating human bone mass for diag...

Probing the molecular mechanisms of α-synuclein inhibitors unveils promising natural candidates through machine-learning QSAR, pharmacophore modeling, and molecular dynamics simulations.

Parkinson's disease is characterized by a multifactorial nature that is linked to different pathways...

CellSighter: a neural network to classify cells in highly multiplexed images.

Multiplexed imaging enables measurement of multiple proteins in situ, offering an unprecedented oppo...

A Review of the Systemic Manifestations of Hepatitis B Virus Infection, Hepatitis D Virus, Hepatocellular Carcinoma, and Emerging Therapies.

Chronic hepatitis B virus (HBV) infection affects about 262 million people worldwide, leading to ove...

Identifying key factors in cell fate decisions by machine learning interpretable strategies.

Cell fate decisions and transitions are common in almost all developmental processes. Therefore, it ...

A hierarchical self-attention-guided deep learning framework to predict breast cancer response to chemotherapy using pre-treatment tumor biopsies.

BACKGROUND: Pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) has demonstrated ...

Machine learning-based model predictive controller design for cell culture processes.

The biopharmaceutical industry continuously seeks to optimize the critical quality attributes to mai...

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.

Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering th...

The prediction of drug sensitivity by multi-omics fusion reveals the heterogeneity of drug response in pan-cancer.

Cancer drug response prediction based on genomic information plays a crucial role in modern pharmaco...