Oncology/Hematology

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

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Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors.

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for th...

Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis.

Screening for prostate cancer relies on the serum prostate-specific antigen test, which provides a h...

Artificial intelligence and hybrid imaging: the best match for personalized medicine in oncology.

Artificial intelligence (AI) refers to a field of computer science aimed to perform tasks typically ...

Immune profile of the tumor microenvironment and the identification of a four-gene signature for lung adenocarcinoma.

The composition and relative abundances of immune cells in the tumor microenvironment are key factor...

Impacts of speciation and extinction measured by an evolutionary decay clock.

The hypothesis that destructive mass extinctions enable creative evolutionary radiations (creative d...

miRNA-Based Feature Classifier Is Associated with Tumor Mutational Burden in Head and Neck Squamous Cell Carcinoma.

Tumor mutation burden (TMB) is considered to be an independent genetic biomarker that can predict th...

Computerized Classification of Prostate Cancer Gleason Scores from Whole Slide Images.

Histological Gleason grading of tumor patterns is one of the most powerful prognostic predictors in ...

Robotic radical prostatectomy: analysis of midterm pathologic and oncologic outcomes: A historical series from a high-volume center.

BACKGROUND: Identifying predictors of positive surgical margins (PSM) and biochemical recurrence (BC...

[Robot-Assisted Right Hemihepatectomy for Hepatocellular Carcinoma].

Since the introduction of robot-assisted surgery, increasingly complex operations have been performe...

Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Preoperative Diffusion-Weighted MR Using Deep Learning.

RATIONALE AND OBJECTIVES: To investigate the value of diffusion-weighted magnetic resonance imaging ...

Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.

Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation o...

Impact of artificial intelligence on colorectal polyp detection.

Since colonoscopy and polypectomy were introduced, Colorectal Cancer (CRC) incidence and mortality d...

The LEukemia Artificial Intelligence Program (LEAP) in chronic myeloid leukemia in chronic phase: A model to improve patient outcomes.

Extreme gradient boosting methods outperform conventional machine-learning models. Here, we have dev...

Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning.

This study aimed to investigate the predictive efficacy of positron emission tomography/computed tom...

IoMT-Based Automated Detection and Classification of Leukemia Using Deep Learning.

For the last few years, computer-aided diagnosis (CAD) has been increasing rapidly. Numerous machine...

Continual improvement of nasopharyngeal carcinoma segmentation with less labeling effort.

PURPOSE: Convolutional neural networks (CNNs) offer a promising approach to automated segmentation. ...

Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects.

We present comboFM, a machine learning framework for predicting the responses of drug combinations i...

Artificial intelligence applications for oncological positron emission tomography imaging.

Positron emission tomography (PET), a functional and dynamic molecular imaging technique, is general...

Deep learning-based radiomics predicts response to chemotherapy in colorectal liver metastases.

PURPOSE: The purpose of this study was to develop and validate a deep learning (DL)-based radiomics ...

Breast Tumor Classification in Ultrasound Images Using Combined Deep and Handcrafted Features.

This study aims to enable effective breast ultrasound image classification by combining deep feature...

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