Oncology/Hematology

Deciphering colorectal cancer radioresistance and immune microrenvironment: unraveling the role of EIF5A through single-cell RNA sequencing and machine learning.

BACKGROUND: Radiotherapy (RT) is a critical component of treatment for locally advanced rectal cance...

Deep neural networks integrating genomics and histopathological images for predicting stages and survival time-to-event in colon cancer.

MOTIVATION: There exists an unexplained diverse variation within the predefined colon cancer stages ...

Machine learning-assisted diagnosis of parotid tumor by using contrast-enhanced CT imaging features.

PURPOSE: This study aims to develop a machine learning diagnostic model for parotid gland tumors bas...

Serum targeted metabolomics uncovering specific amino acid signature for diagnosis of intrahepatic cholangiocarcinoma.

Intrahepatic cholangiocarcinoma (iCCA) is a hepatobiliary malignancy which accounts for approximatel...

Artificial Intelligence-Enhanced Risk Stratification of Cancer Therapeutics-Related Cardiac Dysfunction Using Electrocardiographic Images.

BACKGROUND: Risk stratification strategies for cancer therapeutics-related cardiac dysfunction (CTRC...

Enhancing metastatic colorectal cancer prediction through advanced feature selection and machine learning techniques.

BACKGROUND AND AIMS: Colorectal cancer (CRC) is the third most prevalent cancer globally, posing a s...

SleepGCN: A transition rule learning model based on Graph Convolutional Network for sleep staging.

BACKGROUND AND OBJECTIVE: Automatic sleep staging is essential for assessing and diagnosing sleep di...

The emerging role of Artificial Intelligence in proton therapy: A review.

Artificial intelligence (AI) has made a tremendous impact in the space of healthcare, and proton the...

Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and...

High-quality expert annotations enhance artificial intelligence model accuracy for osteosarcoma X-ray diagnosis.

Primary malignant bone tumors, such as osteosarcoma, significantly affect the pediatric and young ad...

ConvNext Mitosis Identification-You Only Look Once (CNMI-YOLO): Domain Adaptive and Robust Mitosis Identification in Digital Pathology.

In digital pathology, accurate mitosis detection in histopathological images is critical for cancer ...

Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction.

Magnetic resonance imaging (MRI) is known for its accurate soft tissue delineation of tumors and nor...

Individualized prediction of non-sentinel lymph node metastasis in Chinese breast cancer patients with ≥ 3 positive sentinel lymph nodes based on machine-learning algorithms.

BACKGROUND: Axillary lymph node dissection (ALND) is a standard procedure for early-stage breast can...

Preoperative prediction model of lymph node metastasis in the inguinal and femoral region based on radiomics and artificial intelligence.

OBJECTIVE: To predict preoperative inguinal lymph node metastasis in vulvar cancer patients using a ...

MCMVDRP: a multi-channel multi-view deep learning framework for cancer drug response prediction.

Drug therapy remains the primary approach to treating tumours. Variability among cancer patients, in...

Extracting lung cancer staging descriptors from pathology reports: A generative language model approach.

BACKGROUND: In oncology, electronic health records contain textual key information for the diagnosis...

Single-cell and whole-transcriptome sequencing of lymph node metastasis-related gene signature: a large-scale pan-cancer cohort, machine learning and experimental study: Retraction.

An unsupervised learning model based on CT radiomics features accurately predicts axillary lymph node metastasis in breast cancer patients: diagnostic study.

BACKGROUND: The accuracy of traditional clinical methods for assessing the metastatic status of axil...

A commentary on 'Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine-learning'.

Letter to the Editor 'A real-time augmented reality robot integrated with artificial intelligence for skin tumor surgery - experimental study and case series'.

Machine learning in paediatric haematological malignancies: a systematic review of prognosis, toxicity and treatment response models.

BACKGROUND: Machine Learning (ML) has demonstrated potential in enhancing care in adult oncology. Ho...