Oncology/Hematology

Deep Learning Discovers New Morphological Features while Predicting Genetic Alterations from Histopathology of Papillary Thyroid Carcinoma.

Papillary thyroid carcinoma (PTC) is the most common malignant tumor of the endocrine system. mutations occur in 40-60%, mutations in 10-15%, and different gene fusion events such as fusions in 7-35% of these neoplasms. Artificial intelligence (AI) methods could be used to predict genetic changes from conventional histopathological slides. In this retrospective study, we used two independent ...

Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopy.

In nanostructure extraction, advanced techniques like synchrotron radiation and electron microscopy are often hindered by radiation damage and charging artifacts from long exposure times. This study presents a multiframe superresolution method using sparse coding to enhance synchrotron radiation microspectroscopy images. By reconstructing high-resolution images from multiple low-resolution ones, e...

Can ChatGPT Provide Patient-Friendly and Reliable Information on Cervical Cancer Screening? A Study of ChatGPT-Generated Information in Polish.

BACKGROUND Cervical cancer (CC) mortality remains a global health problem, and women's awareness of the need for regular CC screening is insufficient....

Recent Advances in Applying Machine Learning to Proton Radiotherapy.

BACKGROUND/OBJECTIVES: In radiation oncology, precision and timeliness of both planning and treatment are paramount values of patient care. Machine le...

Simultaneous determination of 7 thiols associated proteins in lymphoma patients'serum and cerebrospinal fluid by UHPLC-HRMS technique.

Thiol compounds can serve as markers for the antioxidant and prognostic status of lymphoma, playing a crucial role in early tumor diagnosis. However, ...

Multiclass leukemia cell classification using hybrid deep learning and machine learning with CNN-based feature extraction.

Leukemia is the most prevalent form of blood cancer, affecting individuals across all age groups. Early and accurate diagnosis is crucial for effectiv...

Exploring the impact of neutrophils on lung adenocarcinoma using Mendelian randomization and transcriptomic study.

Tumor immune microenvironment plays a crucial role in determining the prognosis of lung adenocarcinoma (LUAD), with the interaction of immune cells wi...

Machine learning-assisted multi-dimensional transcriptomic analysis of cytoskeleton-related molecules and their relationship with prognosis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, with a poor prognosis due to its aggressive nature and limited tr...

Development of a prediction model by combining tumor diameter and clinical parameters of adrenal incidentaloma.

When adrenal incidentalomas are detected, diagnostic procedures are complicated by the need for endocrine-stimulating tests and imaging using various ...

Folate metabolism-associated CYP26A1 is a clinico-immune target in colorectal cancer.

Folic acid plays a crucial role in cellular regulation and metabolism, commonly included in dietary supplements. Despite this, its involvement in colo...

Comparative analysis of artificial intelligence tools for the dissemination of colorectal cancer screening guidelines: a novel perspective on early screening education.

This study systematically evaluated the effectiveness of three artificial intelligence (AI) tools-ChatGPT-4o, Claude3.5, and DeepSeek-in disseminating...

An automated machine-learning model for prognostic risk stratification of intermediate-stage hepatocellular carcinoma after transarterial chemoembolization.

BACKGROUND: Currently, there is still a lack of noninvasive, automated, and accurate machine-learning(ML) model for prognostic risk stratification of ...

Genetic features for drug responses in cancer - Investigating an ensemble-feature-selection approach.

Predicting drug responses using genetic and transcriptomic features is crucial for enhancing personalized medicine. In this study, we implemented an e...

Assessment of established prognostic factors and artificial intelligence-based evaluation of tumor-infiltrating lymphocytes in oral tongue squamous cell carcinoma.

BACKGROUND: Traditional risk assessment for tongue cancer relies on clinicopathological parameters. Although tumor-infiltrating lymphocytes (TILs) are...

SPACE: Subregion Perfusion Analysis for Comprehensive Evaluation of Breast Tumor Using Contrast-Enhanced Ultrasound-A Retrospective and Prospective Multicenter Cohort Study.

OBJECTIVE: To develop a dynamic contrast-enhanced ultrasound (CEUS)-based method for segmenting tumor perfusion subregions, quantifying tumor heteroge...

A Novel Two-step Classification Approach for Differentiating Bone Metastases From Benign Bone Lesions in SPECT/CT Imaging.

RATIONALE AND OBJECTIVES: This study aims to develop and validate a novel two-step deep learning framework for the automated detection, segmentation, ...

Informatics at the Frontier of Cancer Research.

Digitized healthcare data, high-throughput profiling technologies, and data repositories have facilitated the emergence of a new era of cancer researc...

Intelligent assistant in radiation protection based on large language model with knowledge base.

Radiation protection is a critical pillar supporting the use of nuclear energy and nuclear technologies. The radiation protection system has been esta...

Diagnostic performance of artificial intelligence based on contrast-enhanced computed tomography in pancreatic ductal adenocarcinoma: a systematic review and meta-analysis.

PURPOSE: This meta-analysis systematically evaluated the diagnostic performance of artificial intelligence (AI) based on contrast-enhanced computed to...

Sitting time and risk of cancer incidence and cancer mortality in postmenopausal women: the Women's Health Accelerometry Collaboration.

PURPOSE: Few studies have explored whether accelerometer-measured sedentary behavior increases cancer risk. We examined the associations of accelerome...