Oncology/Hematology

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

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Bladder Cancer and Artificial Intelligence: Emerging Applications.

Bladder cancer is a common and heterogeneous disease that poses a significant burden to the patient ...

Infrastructure tools to support an effective Radiation Oncology Learning Health System.

PURPOSE: Radiation Oncology Learning Health System (RO-LHS) is a promising approach to improve the q...

Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination.

Proteins play a crucial role in many biological processes, where their interaction with other protei...

Optical imaging technologies for cancer detection in low-resource settings.

Cancer continues to affect underserved populations disproportionately. Novel optical imaging technol...

Deep learning analysis of mid-infrared microscopic imaging data for the diagnosis and classification of human lymphomas.

The present study presents an alternative analytical workflow that combines mid-infrared (MIR) micro...

[Artificial Intelligence for computer-aided leukemia diagnostics].

The manual examination of blood and bone marrow specimens for leukemia patients is time-consuming an...

Personalising monitoring for chemotherapy patients through predicting deterioration in renal and hepatic function.

BACKGROUND: In those receiving chemotherapy, renal and hepatic dysfunction can increase the risk of ...

Advancing prostate cancer detection: a comparative analysis of PCLDA-SVM and PCLDA-KNN classifiers for enhanced diagnostic accuracy.

This investigation aimed to assess the effectiveness of different classification models in diagnosin...

Biology-guided deep learning predicts prognosis and cancer immunotherapy response.

Substantial progress has been made in using deep learning for cancer detection and diagnosis in medi...

An overview of ultrasound-derived radiomics and deep learning in liver.

Over the past few years, developments in artificial intelligence (AI), especially in radiomics and d...

Utility and safety of robot-assisted radical cystectomy in older patients with bladder cancer.

This study aimed to investigate the efficacy and safety of robot-assisted radical cystectomy (RARC)...

Robust deep learning-based PET prognostic imaging biomarker for DLBCL patients: a multicenter study.

OBJECTIVE: To develop and independently externally validate robust prognostic imaging biomarkers dis...

Early detection of lung cancer using artificial intelligence-enhanced optical nanosensing of chromatin alterations in field carcinogenesis.

Supranucleosomal chromatin structure, including chromatin domain conformation, is involved in the re...

Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning.

Tumour heterogeneity in breast cancer poses challenges in predicting outcome and response to therapy...

Feature-aware unsupervised lesion segmentation for brain tumor images using fast data density functional transform.

We demonstrate that isomorphically mapping gray-level medical image matrices onto energy spaces unde...

A subcomponent-guided deep learning method for interpretable cancer drug response prediction.

Accurate prediction of cancer drug response (CDR) is a longstanding challenge in modern oncology tha...

Multi-task deep learning-based radiomic nomogram for prognostic prediction in locoregionally advanced nasopharyngeal carcinoma.

PURPOSE: Prognostic prediction is crucial to guide individual treatment for locoregionally advanced ...

Clinical evaluation of deep learning-based automatic clinical target volume segmentation: a single-institution multi-site tumor experience.

PURPOSE: The large variability in tumor appearance and shape makes manual delineation of the clinica...

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