Oncology/Hematology

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

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Bringing Structural Implications and Deep Learning-Based Drug Identification for Mutants.

Colorectal cancer is considered one of the leading causes of death that is linked with the Kirsten R...

Identification of drug combinations on the basis of machine learning to maximize anti-aging effects.

Aging is a multifactorial process that involves numerous genetic changes, so identifying anti-aging ...

A tree-based multiclassification of breast tumor histopathology images through deep learning.

Worldwide, the burden of cancer is drastically increasing over the past few years. Among all types o...

Detecting MLC modeling errors using radiomics-based machine learning in patient-specific QA with an EPID for intensity-modulated radiation therapy.

PURPOSE: We sought to develop machine learning models to detect multileaf collimator (MLC) modeling ...

Wavelet decomposition facilitates training on small datasets for medical image classification by deep learning.

The adoption of low-dose computed tomography (LDCT) as the standard of care for lung cancer screenin...

Application of deep learning for automatic segmentation of brain tumors on magnetic resonance imaging: a heuristic approach in the clinical scenario.

PURPOSE: Accurate brain tumor segmentation on magnetic resonance imaging (MRI) has wide-ranging appl...

Radiomics to better characterize small renal masses.

PURPOSE: Radiomics is a specific field of medical research that uses programmable recognition tools ...

Identifying metastatic ability of prostate cancer cell lines using native fluorescence spectroscopy and machine learning methods.

Metastasis is the leading cause of mortalities in cancer patients due to the spreading of cancer cel...

A deep learning-based model for screening and staging pneumoconiosis.

This study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pne...

Enhancing digital tomosynthesis (DTS) for lung radiotherapy guidance using patient-specific deep learning model.

Digital tomosynthesis (DTS) has been proposed as a fast low-dose imaging technique for image-guided ...

Few-shot learning creates predictive models of drug response that translate from high-throughput screens to individual patients.

Cell-line screens create expansive datasets for learning predictive markers of drug response, but th...

Using natural language processing to explore heterogeneity in moral terminology in palliative care consultations.

BACKGROUND: High quality serious illness communication requires good understanding of patients' valu...

Supervised mutational signatures for obesity and other tissue-specific etiological factors in cancer.

Determining the etiologic basis of the mutations that are responsible for cancer is one of the funda...

Predicting Tumor Cell Response to Synergistic Drug Combinations Using a Novel Simplified Deep Learning Model.

Drug combinations targeting multiple targets/pathways are believed to be able to reduce drug resista...

A Reliable Machine Learning Approach applied to Single-Cell Classification in Acute Myeloid Leukemia.

Machine Learning research applied to the medical field is increasing. However, few of the proposed a...

A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging.

Medical ionizing radiation procedures and especially medical imaging are a non negligible source of ...

Deep learning system for lymph node quantification and metastatic cancer identification from whole-slide pathology images.

BACKGROUND: Traditional diagnosis methods for lymph node metastases are labor-intensive and time-con...

Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia.

Reliable and accurate prediction model capturing the changes in solar radiation is essential in the ...

Machine-Learning Provides Patient-Specific Prediction of Metastatic Risk Based on Innovative, Mechanobiology Assay.

Cancer mortality is mostly related to metastasis. Metastasis is currently prognosed via histopatholo...

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