Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Showing 2689-2709 of 15,318 articles
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...

Machine learning based anoikis signature predicts personalized treatment strategy of breast cancer.

BACKGROUND: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing th...

Integrating artificial intelligence with smartphone-based imaging for cancer detection in vivo.

Cancer is a major global health challenge, accounting for nearly one in six deaths worldwide. Early ...

Automatic discrimination between neuroendocrine carcinomas and grade 3 neuroendocrine tumors by deep learning of H&E images.

Neuroendocrine neoplasms (NENs) arise from diffuse neuroendocrine cells and are categorized as eithe...

Urine Analysed by FTIR, Chemometrics and Machine Learning Methods in Determination Spectroscopy MarkerĀ of Prostate Cancer in Urine.

Prostate-specific antigen (PSA) is the most commonly used marker of prostate cancer. However, nearly...

MetaPhenotype: A Transferable Meta-Learning Model for Single-Cell Mass Spectrometry-Based Cell Phenotype Prediction Using Limited Number of Cells.

Single-cell mass spectrometry (SCMS) is an emerging tool for studying cell heterogeneity according t...

Interpretable Machine Learning Algorithms Identify Inetetamab-Mediated Metabolic Signatures and Biomarkers in Treating Breast Cancer.

BACKGROUND: HER2-positive breast cancer (BC), a highly aggressive malignancy, has been treated with ...

Leveraging Bioinformatics and Machine Learning for Identifying Prognostic Biomarkers and Predicting Clinical Outcomes in Lung Adenocarcinoma.

There exist significant challenges for lung adenocarcinoma (LUAD) due to its poor prognosis and lim...

Comparison of machine learning methods for Predicting 3-Year survival in elderly esophageal squamous cancer patients based on oxidative stress.

BACKGROUND: Oxidative stress process plays a key role in aging and cancer; however, currently, there...

Enhanced MobileNet for skin cancer image classification with fused spatial channel attention mechanism.

Skin Cancer, which leads to a large number of deaths annually, has been extensively considered as th...

In-context learning enables multimodal large language models to classify cancer pathology images.

Medical image classification requires labeled, task-specific datasets which are used to train deep l...

Resolution-dependent MRI-to-CT translation for orthotopic breast cancer models using deep learning.

This study aims to investigate the feasibility of utilizing generative adversarial networks (GANs) t...

Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form.

BACKGROUND AND OBJECTIVE: Detecting patients at high risk of occurrence of an Invasive Disease Event...

Federated Learning for Predicting Postoperative Remission of Patients with Acromegaly: A Multicentered Study.

BACKGROUND: Decentralized federated learning (DFL) may serve as a useful framework for machine learn...

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...

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