Oncology/Hematology

Clinical Decision Support Systems for cancer symptom management: A scoping review.

BACKGROUND: Effective cancer symptom management significantly impacts patient outcomes and quality of life. While Clinical Decision Support Systems show promise for enhancing symptom management, comprehensive analysis of their implementation in nursing practice remains limited. Understanding Clinical Decision Support Systems characteristics is essential for advancing evidence-based nursing impleme...

Deep learning models for image classification of lymphoma: a pilot study in canine.

The aim of this study was to distinguish canine lymphoma from other diseases, particularly reactive lymphoid hyperplasia (RLH), based on fine needle aspiration (FNA) images. We developed four deep learning models based on Vision Transformer (ViT) and Inception-v3, which were pre-trained image classification models. The two models out of four were ViT and Inception-v3, and the remained were the two...

Interpretable machine learning for accessible dysphagia screening and staging in older adults.

Dysphagia in older adults causes serious complications, and efficient and scalable screenings are needed. This prospective multicenter study developed...

Evaluating the ability of AI chatbots to provide informed consent information for common oncological surgeries.

INTRODUCTION: Informed consent is fundamental to oncological surgery, but communication is often hindered by medical terminology, inconsistent explana...

Explainable machine learning model for predicting early recurrence and distant metastasis after surgery in early-onset colorectal cancer.

OBJECTIVE: To develop explainable machine learning models for predicting the risk of early postoperative recurrence and distant metastasis in patients...

Artificial intelligence takes on the multidisciplinary committee: A single-center study for rectal cancer management.

BACKGROUND: As rectal cancer management evolves, the multidisciplinary committee becomes increasingly important in integrating expertise to optimize p...

Biparametric MRI-Based Habitat Analysis Integrated With Deep Learning for Predicting Clinically Significant Prostate Cancer in PI-RADS Category 3 Lesions.

BACKGROUND: Detection of clinically significant prostate cancer (csPCa) within PI-RADS category 3 lesions remains a major diagnostic challenge. PURPOS...

Next-generation multicenter studies: using artificial intelligence to automatically process unstructured health records of patients with lung cancer across multiple institutions.

BACKGROUND: Manual abstraction of real-world data (RWD) from unstructured health records (HRs) remains resource intensive, error prone, and highly var...

Cellular and molecular determinants of lymph node metastasis in papillary thyroid carcinoma: Integrated multi-omics profiling and machine learning models.

The mechanisms underlying lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) remain elusive. This study integrated single-cell RNA seque...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vasculature, limiting drug delivery and immune infiltrati...

Artificial Intelligence in Pediatric Oncology Care: Pediatric Nurses' Perspectives and Future Implications.

OBJECTIVES: This study aimed to explore pediatric oncology nurses' perspectives on the integration of artificial intelligence (AI) into pediatric onco...

Interpretable fusion deep learning on super-resolution MRI for perineural invasion prediction in pancreatic ductal adenocarcinoma: a multicenter study.

PURPOSE: To develop an interpretable fusion deep learning model based on super-resolution (SR) MRI for predicting preoperative perineural invasion (PN...

Clinical practice, barriers to implementation, and priorities for equitable access of Stereotactic Body Radiation Therapy: An analysis of the global status by the ESTRO SBRT Focus Group.

BACKGROUND: Stereotactic Body Radiation Therapy (SBRT) has become an established treatment for several primary and metastatic malignancies; however, c...

Multimodality Artificial Intelligence for Involved-Site Radiation Therapy: Clinical Target Volume Delineation in High-Risk Pediatric Hodgkin Lymphoma.

PURPOSE: Clinical target volume (CTV) delineation for involved-site radiation therapy (ISRT) in Hodgkin lymphoma (HL) is time-consuming because of the...

Multi-center-validated machine learning model for cervical cancer based on human papillomavirus genotyping results.

OBJECTIVE: Cervical cancer remains a leading cause of gynecologic cancer-related mortality worldwide, with human papillomavirus (HPV) testing being a ...

Use of gadolinium-based contrast agents in head and neck cancer diagnosis, staging, and monitoring: current applications and future perspectives.

Gadolinium-based contrast agents (GBCAs) have been fundamental to head and neck cancer (HNC) imaging, enabling effective detection, characterization, ...

FRET-SAM: SAM_Med2D-based automatic FRET two-hybrid analysis.

BACKGROUND AND OBJECTIVE: The fluorescence resonance energy transfer (FRET) two-hybrid assay enables quantification of the stoichiometry and binding a...

A novel multimodal diagnostic framework integrating hyperspectral imaging and deep learning for predicting RET gene mutations in medullary thyroid carcinoma.

BACKGROUND AND OBJECTIVE: Medullary thyroid carcinoma (MTC) is an aggressive malignancy driven predominantly by activating mutations in the RET proto-...

Aspartame promotes ovarian cancer progression: A multi-omics study integrating mendelian randomization, network toxicology, and in vitro validation.

The causal relationship between the artificial sweetener aspartame and ovarian cancer (OC), a highly lethal malignancy, remains unclear. This study, t...

Circadian rhythm: An emerging force for colorectal cancer treatment.

The relationship between circadian rhythm disorder and the occurrence and progression of colorectal cancer (CRC) has received attention. The circadian...