Oncology/Hematology

[Neck dissection-more, less, targeted?].

Neck dissection is an essential part of surgical treatment for head and neck malignancies. In recent years, the extent of neck dissection required for optimal oncological results has been increasingly reduced and, in some cases, replaced by alternative procedures such as sentinel lymph node biopsy. However, this is only possible with precise staging. Improved imaging, molecular markers, and artifi...

Integrating AI-driven technologies and facial-semantic features for depression detection: A cross-sectional study.

BACKGROUND: Depression is a major global health concern, still individuals with depressive tendencies remain undetected in outpatient settings due to the limitations of self-report, stigma, and reporting bias. Advances in artificial intelligence (AI) offer opportunities for objective, scalable, and unobtrusive methods of early detection. This study examined predictive accuracy of two AI-driven sys...

Disease and state dependent neural markers in adolescents with BD. Understanding the neural bases of mania, depression and remission in a data fusion approach.

BACKGROUND: Pediatric bipolar disorder (PBD) is a severe and disabling condition marked by alternating episodes of mania and depression, intermitted w...

The actual performance of ML/AI models in predicting radiation-induced toxicity in head and neck cancer: a systematic review and meta-analysis.

An increasing number of Artificial intelligence (AI) and machine learning (ML) models are being developed to predict radiation-induced toxicities (RIT...

Senescence-related gene signature predicts prostate cancer progression and identifies PCNA as a therapeutic target via multi-omics machine learning integration.

BACKGROUND: Senescence plays a critical role in prostate cancer, influencing disease onset and progression. However, the alterations of senescence-ass...

Development of Digital Literacy: Application of Artificial Intelligence in Education and Clinical Practice of Oncology Nurses.

OBJECTIVES: To synthesize current educational approaches to AI literacy in oncology nursing, identify key competency domains along with barriers and e...

Primary tissue metabolic fingerprinting for efficient diagnosis of lymph node metastasis and metabolic reprogramming mechanisms in colorectal cancer.

Accurate detection of lymph node metastasis (LNM) is critical for colorectal cancer (CRC) staging and treatment planning, yet current histopathologica...

Bayesian selection of lipidome dynamics features for a K-nearest neighbors (KNN) classifier model of tumor response in patients with advanced gastrointestinal adenocarcinoma undergoing systemic treatment.

BACKGROUND: Dysregulated lipid metabolism is common in patients with gastrointestinal (GI) cancer. This study investigated the ability of plasma lipid...

BRAIN-META: A reproducible CNN-vision transformer meta-ensemble pipeline for explainable brain tumor classification.

This study presents BRAIN-META, a reproducible deep learning methodology designed for multi-class brain tumor classification using structural MRI. The...

A deep learning framework to stratify Nottingham histologic grade 2 breast tumors based on dynamic contrast-enhanced MRI.

OBJECTIVE: The Nottingham Histologic Grade (NHG) informs prognosis and treatment decisions in breast cancer, but NHG2 tumors are biologically heteroge...

Interobserver variability in histopathologic diagnosis of melanocytic neoplasms.

BACKGROUND: Precise histopathologic diagnosis of melanocytic neoplasms is required to guide appropriate clinical management; however, significant inte...

TEWS: Transformer-empowered weakly supervised prediction of immune score and genetic mutations in liver cancer from whole slide image.

Whole Slide Imaging (WSI) plays a crucial role in predicting immune scores by providing detailed cellular and tissue-level insights, thereby enhancing...

Navigating the winding road toward precision prostate cancer care.

Prostate cancer (PCa) remains the second leading cause of cancer-related mortality among U.S. men, driven in large part by metastatic castration-resis...

A hybrid framework integrating serum biochemical markers and FTIR spectroscopy with machine learning for early cancer screening.

Early detection of cancer remains a key challenge in clinical diagnosis. This study explored two serum sample-based early cancer screening methods: on...

The basis for future personalized therapy approaches - Machine learning-generated 1-year survival rate, metastatic status and therapy-dependent survival in pancreatic cancer patients.

BACKGROUND: Pancreatic adenocarcinoma (PDAC) remains one of the most lethal types of cancer, characterized by its unspecific symptoms, aggressive natu...

An interpretable model based on weakly supervised learning for uterine smooth muscle tumor diagnosis: A multi-center study.

Uterine smooth muscle tumors (USMTs) are the most common tumors of the female reproductive system, but remain diagnostically challenging due to morpho...

Revealing the anti-tumor mechanisms of aromatic oil from Amomum villosum through integrated network pharmacology, bioinformatics, machine learning, single-cell sequencing, and cell experiments.

The dry fruits of Amomum villosum (Av) are a traditional Chinese medicine used for gastrointestinal disease. Aromatic oil has been reported to have an...

Integrative analysis of transcriptomic data reveals a predictive gene signature for chemoradiotherapy response in rectal cancer.

Locally advanced rectal cancer (LARC) is treated with neoadjuvant chemoradiotherapy (nCRT), but only a minority of patients achieve a pathological com...

Regional-aware and sequence-informed multi-decoder network for robust brain glioma segmentation in multi-parametric MRI.

Accurate segmentation of glioblastoma subregions from multi-parametric MRI is essential for diagnosis, surgical planning, and treatment monitoring in ...

Amentoflavone from Ginkgo biloba inhibits EMT-driven lung cancer metastasis by targeting TGFBR2: Integrative network pharmacology, machine learning, and experimental validation.

ETHNOPHARMACOLOGICAL RELEVANCE: In non-small cell lung cancer (NSCLC), fatal outcomes predominantly result from metastatic dissemination, highlighting...