Other Cancers

Assessment of the risk of bacteremia in patients with hematologic malignancies in the emergency department: A comparative study between logistic regression and machine learning algorithms.

OBJECTIVE: To stratify the risk of bacteremia at the time of emergency department (ED) admission in patients with hematologic malignancies. To this end, we compared the performance of unsupervised and supervised machine learning algorithms with the classical multivariable logistic regression model. METHODS: We conducted a multicenter, international, retrospective cohort study including consecutive...

Interpretable LightGBM model with SHAP analysis predicts non-excellent response to initial radioiodine therapy in differentiated thyroid carcinoma.

PURPOSE: To identify independent determinants influencing therapeutic outcomes of initial radioactive iodine (1 3 1I) therapy in differentiated thyroid carcinoma (DTC) and establish an interpretable predictive framework for clinical decision-making. MATERIALS AND METHODS: A retrospective cohort of 950 treatment-naïve DTC patients undergoing primary 1 3 1I therapy was randomly allocated into traini...

Usefulness of Artificial Intelligence for Surgical Support in Robot-assisted Distal Pancreatectomy: A Preliminary Case Report.

BACKGROUND/AIM: The incidence of postoperative complications in minimally-invasive surgery for pancreatic disease remains a concern. The application o...

Deep Learning for Automated Tumor Segmentation of Rectal Cancer on T2-Weighted Magnetic Resonance Images.

PURPOSE: To develop a deep learning (DL)-based automated segmentation model for rectal cancer on T2-weighted (T2W) magnetic resonance (MR) images. MAT...

Arrhythmias and cardiac devices management in oncology patients.

Cardiac arrhythmia is increasingly encountered in patients with cancer, not only as a result of shared risk factors but also as a direct consequence o...

A 3D morphogenetic blueprint for metastatic outgrowth in breast cancer.

The tissue-level processes underpinning metastatic outgrowth remain unclear. We combined single-cell RNA sequencing, spatial transcriptomics, and AI-s...

A metabolite-augmented FIB-4 machine learning panel achieves superior liver fibrosis staging in chronic liver disease.

Accurate, non-invasive liver fibrosis detection is essential for chronic liver disease management, particularly with rising metabolic dysfunction-asso...

A high-speed attention network for MHC-bound peptide identification and 3D modeling.

We developed SwiftMHC, an ultra-fast and accurate structure-based framework for peptide-MHC (pMHC) modeling and binding affinity prediction. Using tas...

Neurosurgical Application of Artificial Intelligence in Pediatric Neuro-Oncology.

Pediatric neuro-oncology is a critical field of neurosurgery, representing the leading cause of disease-related mortality in children. Despite its rar...

Short-chain fatty acid-producing microbes differentiate non-infectious and infectious neutropenic fever in leukemia.

UNLABELLED: Neutropenic fever (NF) is often the first sign of infection in patients with hematologic malignancies, but its cause is frequently unknown...

Testosterone-Sparing Treatment Strategies for Biochemically Recurrent Prostate Cancer After Radical Prostatectomy.

PURPOSE OF REVIEW: Biochemical recurrence (BCR) after radical prostatectomy occurs in up to one-third of patients and increases the risk of metastasis...

AI-assessed sarcopenia as an independent predictor of neoadjuvant chemotherapy outcomes in muscle-invasive bladder cancer.

PURPOSE: Sarcopenia has already been widely investigated as a potential indicator of negative outcomes in oncology patients. Our aim was to evaluate t...

The Impact of Data Consistency on Deep Learning Models for Nasopharyngeal Cancer Organ Auto-Segmentation.

PURPOSE: To investigate how annotation consistency influences deep learningbased auto-contouring performance for organs-at-risk (OARs) in nasopharynge...

A Multitask Deep Learning Approach for Tumor Segmentation and Morphological Quantification in Acral Melanoma Whole-Slide Images.

This study presents an integrated multitask deep learning framework for the automated analysis of acral melanoma from whole-slide images (WSIs). We co...

Perspectives from machine learning and multi-omics to decoding the effects of VDAC2 malignant subsets on tumor evolution.

VDAC2's known role in cancer and immune regulation via enhancing the CD8+ T cell-mediated killing, and it is worth systematically digging out the role...

Rapid and noninvasive artificial intelligence-assisted diagnostic method for oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) remains the most common head and neck malignancy, for which early detection is critical yet challenging with curre...

[Machine learning and radiomics-based model for predicting response to lenvatinib combined with TACE in patients with unresectable hepatocellular carcinoma].

Objective: To evaluate the predictive value of machine learning combined with radiomics for treatment response to lenvatinib combined with transarteri...

Inflammatory-nutritional biomarker scores and risk of malignant effusion in a pan-cancer cohort of 68,916 patients: Nonlinear associations and machine learning validation.

PURPOSE: Inflammatory-nutritional biomarker scores derived from routine blood tests have established prognostic value in cancer, yet their association...

High-accuracy instance segmentation of cellular structures in head and neck squamous cell carcinoma histopathology using a cyto R-CNN deep learning framework.

This study develops a deep learning-based model to automate the instance segmentation of nuclei and whole cells in hematoxylin and eosin-stained head ...

Animal Models of Allergen Immunotherapy for Allergic Airway Inflammation.

Allergen immunotherapy (AIT) is currently the only disease-modifying therapy for allergic airway inflammation. However, its underlying mechanisms rema...