Oncology/Hematology

Evaluating the efficacy of using large language models in preoperative prediction of microvascular invasion in HCC: a multicenter study.

Primary liver cancer is the sixth most commonly diagnosed cancer globally and the third leading caus...

Comparing non-machine learning vs. machine learning methods for Ki67 scoring in gastrointestinal neuroendocrine tumors.

The Ki67 score is a crucial prognostic biomarker for neuroendocrine tumors, but its manual assessmen...

K-Means Clustering and Classification of Breast Cancer Images Using Histogram of Oriented Gradients Features and Convolutional Neural Network Models: Diagnostic Image Analysis Study.

BACKGROUND: Breast cancer has proven to be the most common type of cancer among females around the w...

Anomaly detection using intraoperative iKnife data: a comparative analysis in breast cancer surgery.

PURPOSE: Intraoperative margin assessment is crucial to ensure complete tumor removal and minimize t...

Noninvasive and Sensitive Biosensor for the Detection of Oral Cancer Prognostic Biomarkers.

Early detection of oral squamous cell carcinoma (OSCC) significantly enhances treatment outcomes and...

Machine Learning for Prediction of High-Risk Hospitalizations in Lymphoma Patients: A Danish Population-Based Study.

OBJECTIVE: Infections are a leading cause of hospitalization in patients treated for lymphoma and ca...

Plasmonic Fiber Optic Sensing Platform for Point-of-Care Pharmacokinetic Monitoring of Platinum Chemotherapeutics: Toward Ultratrace Multi-omics Precision Chemotherapy Management.

Precision chemotherapy management requires efficient and ultrasensitive dynamic monitoring of drug p...

Sensitive Detection and Identification Method of Erythrocyte-like Cells upon Doxorubicin Induced Differentiation with Vibrational Techniques.

Altered differentiation of blood cell precursors and their clonal expansion occurs in various types ...

Radiomics meets transformers: A novel approach to tumor segmentation and classification in mammography for breast cancer.

ObjectiveThis study aimed to develop a robust framework for breast cancer diagnosis by integrating a...

Advancements in DNA methylation technologies and their application in cancer diagnosis.

DNA methylation is a common epigenetic modification that maintains the integrity of the DNA sequence...

Commentary: Artificial intelligence and machine learning in ocular oncology, retinoblastoma - A balanced perspective.

Radiomics with Machine Learning Improves the Prediction of Microscopic Peritumoral Small Cancer Foci and Early Recurrence in Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: This study aimed to develop an interpretable machine learning model using ...

Unveiling key pathomic features for automated diagnosis and Gleason grade estimation in prostate cancer.

BACKGROUND: Recent advances in histology scanning technology and Artificial Intelligence (AI) offer ...

Evaluating crop yield prediction models in illinois using aquacrop, semi-physical model and artificial neural networks.

Crop yield is important for agricultural productivity and the country's economy. While crop yield es...

A bibliometric analysis reveals a dynamic growth in the use of artificial intelligence in oral cancer research over three decades.

Oral cancer (OC) remains a significant malignant neoplasm in both the developed and developing world...

Machine learning-based MRI imaging for prostate cancer diagnosis: systematic review and meta-analysis.

OBJECTIVE: This study aims to evaluate the diagnostic value of machine learning-based MRI imaging in...

A new low-rank adaptation method for brain structure and metastasis segmentation via decoupled principal weight direction and magnitude.

Deep learning techniques have become pivotal in medical image segmentation, but their success often ...

Gut microbiota and SCFAs improve the treatment efficacy of chemotherapy and immunotherapy in NSCLC.

The role of gut dysbiosis in shaping immunotherapy responses is well-recognized, yet its effect on t...

Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection.

Breast cancer is a relatively common carcinoma among women worldwide and remains a considerable publ...

protPheMut: An Interpretable Machine Learning Tool for Classification of Cancer and Neurodevelopmental Disorders in Human Missense Mutations.

Recent advances in human genomics have revealed that missense mutations in a single protein can lead...

Detecting and classifying the mechanics of cancer and non-cancer cells by machine learning algorithm.

The global burden of cancer has increased in recent years, posing a major public health challenge. G...