Hematology

Leukemia

Latest AI and machine learning research in leukemia for healthcare professionals.

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Exploring an novel diagnostic gene of trastuzumab-induced cardiotoxicity based on bioinformatics and machine learning.

Trastuzumab (Tra)-induced cardiotoxicity (TIC) is a serious side effect of cancer chemotherapy, whic...

Predicting chemotherapy responsiveness in gastric cancer through machine learning analysis of genome, immune, and neutrophil signatures.

BACKGROUND: Gastric cancer is a major oncological challenge, ranking highly among causes of cancer-r...

Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population.

BACKGROUND: Manually extracted imaging-based body composition measures from a single-slice area (A) ...

Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy.

BACKGROUND: Lung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and...

Machine learning methods to identify risk factors for corneal graft rejection in keratoconus.

Machine learning can be used to identify risk factors associated with graft rejection after corneal ...

Leveraging AI models for lesion detection in osteonecrosis of the femoral head and T1-weighted MRI generation from radiographs.

This study emphasizes the importance of early detection of osteonecrosis of the femoral head (ONFH) ...

Automated workflow for the cell cycle analysis of (non-)adherent cells using a machine learning approach.

Understanding the cell cycle at the single-cell level is crucial for cellular biology and cancer res...

Using Machine Learning Models to Predict Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

PURPOSE: Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling i...

A Multi-task learning U-Net model for end-to-end HEp-2 cell image analysis.

Antinuclear Antibody (ANA) testing is pivotal to help diagnose patients with a suspected autoimmune ...

Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with...

Artificial intelligence model for predicting sexual dimorphism through the hyoid bone in adult patients.

The objective of this study was to develop a predictive model using supervised machine learning to d...

Diagnosis and typing of leukemia using a single peripheral blood cell through deep learning.

Leukemia is highly heterogeneous, meaning that different types of leukemia require different treatme...

Explainable machine learning models for predicting the acute toxicity of pesticides to sheepshead minnow (Cyprinodon variegatus).

A quantitative structure-activity relationship (QSAR) study was conducted on 313 pesticides to predi...

Exploring the role of Artificial Intelligence in Acute Kidney Injury management: a comprehensive review and future research agenda.

This study reviews the studies utilizing Artificial Intelligence (AI) and AI-driven tools and method...

Prediction of acute respiratory infections using machine learning techniques in Amhara Region, Ethiopia.

Many studies have shown that infectious diseases are responsible for the majority of deaths in child...

Generalizable self-supervised learning for brain CTA in acute stroke.

Acute stroke management involves rapid and accurate interpretation of CTA imaging data. However, gen...

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