Oncology/Hematology

A deep-learning framework for brain tumor segmentation via three-dimensional mass-preserving geometric transformation.

This article presents a robust and efficient framework for brain tumor segmentation based on deep learning. We introduce a novel three-dimensional (3D) mass-preserving geometric transformation (MPGT) that employs a homotopy method to transform irregular brain magnetic resonance (MR) images into standardized solid cubes. This transformation preserves local mass ratios while maintaining global struc...

The density of tumour infiltrating lymphocytes in oesophago-gastric cancer varies with disease stage, geographical region and treatment: a post hoc analysis of nine phase III clinical trials.

BACKGROUND: Tumour infiltrating lymphocytes (TILs) are a key component of the tumour microenvironment. To establish a clinically relevant TILs cut-off for patients with oesophago-gastric (OG) cancer, it is essential to know whether TILs density varies by patient and/or disease characteristics. MATERIALS AND METHODS: TILs were quantified as TILs/mm2 (TILs density) by a deep-learning algorithm appli...

A framework for quantifying and leveraging uncertainty in pre-trained CT denoising model.

OBJECTIVE: To develop an architecture-agnostic framework that estimates, calibrates, and leverages total uncertainty (aleatoric + epistemic) in pre-tr...

Learning Drug Synergy through Environment-Conditioned Feature Modulation.

MOTIVATION: Drug combinations are crucial for overcoming resistance in cancer therapy. Although deep learning has achieved strong performance in syner...

Development and validation of a machine learning model to predict recurrence in polypoidal choroidal vasculopathy: a multicentre prospective study.

AIM: This study aims to develop and validate machine learning models for predicting recurrence in polypoidal choroidal vasculopathy (PCV) patients usi...

Machine learning for the prediction of three-year survival in locally advanced breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound imaging.

Locally Advanced Breast Cancer (LABC) is a serious type of cancer with a poor prognosis despite advances in cancer treatment. As the disease is often ...

Transformer based breast cancer classification from histopathological images using sequential residual recurrent multiscale attention network.

Breast cancer is a leading cause of mortality among women globally, highlighting the need for accurate and robust diagnostic systems. This study prese...

Comprehensive evaluation of cross cancer generalization in histopathology segmentation models across 21 tumor types.

BACKGROUND: Artificial intelligence has significantly advanced computational pathology by enabling high-resolution, clinical-grade tumor segmentation ...

Pancreatic tumor detection in computed tomography images through a rotary positional siamese vision transformer.

Vision Transformers (ViTs) are one of the powerful tools in medical imaging, providing new possibilities for pancreatic cancer diagnosis. In recent ye...

Prediction of tumor regression grading in rectal cancer neoadjuvant chemoradiotherapy: a habitat radiomics analysis of imaging biomarker.

BACKGROUND: Tumor regression grading (TRG) is a core prognostic predictor of treatment outcomes in rectal cancer. Conventional TRG assessment methods ...

Evaluating the clinical safety of large language models in oral cancer-related patient communication: a repeated-prompt observational study.

BACKGROUND: As patients increasingly consult large language models (LLMs) for health-related information, evaluating the clinical safety of AI-generat...

Construction of a risk scoring model based on machine learning and validation of the role of the key gene SERPINE1 in the progression of colon cancer.

BACKGROUND AND OBJECTIVE: Colon cancer (CC) is a highly prevalent malignant tumor with a high mortality rate worldwide. Despite recent advancements in...

Integrating multi-omics and machine learning to decipher the molecular pathways of bisphenol a-associated lactylation-related genes driving bladder cancer.

In this study, we systematically investigated bladder cancer-related gene signatures using a toxicogenomics-informed framework, with particular attent...

A systematic review and meta-analysis of medical image-based artificial intelligence models for predicting metastasis in ovarian cancer.

OBJECTIVE: To conduct a systematic review and meta-analysis evaluating the diagnostic performance of medical image-based artificial intelligence (AI) ...

Dynamic changes in gut microbiota and discovery of prognostic biomarkers in locally advanced pancreatic cancer during chemoradiotherapy.

UNLABELLED: Pancreatic cancer has an exceptionally poor prognosis, with the majority of cases diagnosed at an advanced stage. Concurrent chemoradiothe...

Protocol for cerebrospinal fluid analysis using enrichment-enhanced surface-enhanced Raman spectroscopy and transformer-enabled spectral classification.

The rapid detection and precise classification of cerebrospinal fluid in acute leukemia patients constitute a crucial clinical imperative. Here, we pr...

Relational-temporal dignity at the end of life: Ethical foundations for the DiRePal model in the algorithmic age.

OBJECTIVES: The increasing presence of artificial intelligence (AI), electronic patient-reported outcomes (ePROMs), and digital infrastructures in pal...

MRI Deep Learning for Differentiating Glioblastoma, IDH-Wildtype from Central Nervous System Diffuse Large B-cell Lymphoma.

Glioblastoma, IDH-wildtype (GBM) and central nervous system diffuse large B-Cell lymphoma (CNS-DLBCL) are aggressive brain tumors with overlapping MRI...

Physician Perspectives on ChatGPT-4o as a Patient Resource for Abdominal Cancer Surgeries: Cross-Sectional Survey.

BACKGROUND: Artificial intelligence (AI) models are being increasingly integrated into clinical care. Moreover, the availability of publicly accessibl...

Understanding LUng Cancer risk factors and their Impact Assessment (LUCIA): protocol for multicentre observational cohort study.

INTRODUCTION: Lung cancer (LC) is the leading cause of cancer-related mortality worldwide, primarily due to diagnosis at advanced stages. Although low...