Oncology/Hematology

[Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].

Cone-beam computed tomography (CBCT) is widely used in dentistry, surgery, radiotherapy and other medical fields. However, repeated CBCT scans expose patients to additional radiation doses, increasing the risk of secondary malignant tumors. Low-dose CBCT image reconstruction technology, which employs advanced algorithms to reduce radiation dose while enhancing image quality, has emerged as a focal...

[Progress in neoadjuvant immunotherapy for locally advanced rectal cancer].

Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (LARC), yet the pathological complete response (pCR) rates remain suboptimal. The introduction of immunotherapy has opened new avenues for LARC management, particularly in patients with mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H) status. In this subset, anti-programme...

FTIR-based machine learning for prediction of malignant transformation in oral epithelial dysplasia.

Oral squamous cell carcinoma (OSCC) is an aggressive cancer with a poor prognosis. Oral epithelial dysplasia (OED) is a precancerous lesion associated...

How to predict effective drug combinations - moving beyond synergy scores.

To improve our understanding of multi-drug therapies, cancer cell line panels screened with drug combinations are frequently studied using machine lea...

Structure-based artificial intelligence-aided design of MYC-targeting degradation drugs for cancer therapy.

The MYC protein is an oncoprotein that plays a crucial role in various cancers. Although its significance has been well recognized in research, the de...

Blood-based proteomic profiling identifies OSMR as a novel biomarker of AML outcomes.

Inflammation is increasingly recognized as a critical factor in acute myeloid leukemia (AML) pathogenesis. We performed blood-based proteomic profilin...

Automated MRI Tumor Segmentation using hybrid U-Net with Transformer and Efficient Attention

Cancer is an abnormal growth with potential to invade locally and metastasize to distant organs. Accurate auto-segmentation of the tumor and surroun...

Advanced cervical cancer classification: enhancing pap smear images with hybrid PMD Filter-CLAHE

Cervical cancer remains a significant health problem, especially in developing countries. Early detection is critical for effective treatment. Convo...

Quantitative and qualitative metrics of tumor stroma in predicting ovarian cancer outcomes and expansion of its study with AI-based tools.

Epithelial ovarian cancer remains one of the deadliest gynecologic malignancies, with late-stage diagnosis, high recurrence rates, and resistance to p...

Personalized translational medicine: Investigating YKL-40 as early biomarker for clinical risk stratification in hepatocellular carcinoma recurrence post-liver transplantation.

Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) presents a significant challenge, with recurrence rates ranging from 8% to ...

Prediction of bacterial and fungal bloodstream infections using machine learning in patients undergoing chemotherapy.

PURPOSE: This study aimed to develop a machine learning (ML) model to predict bloodstream infection (BSI) in chemotherapy patients.

BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification with Swin-HAFNet

Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remain key challenges in medical image analysis, larg...

ViT-NeBLa: A Hybrid Vision Transformer and Neural Beer-Lambert Framework for Single-View 3D Reconstruction of Oral Anatomy from Panoramic Radiographs

Dental diagnosis relies on two primary imaging modalities: panoramic radiographs (PX) providing 2D oral cavity representations, and Cone-Beam Comput...

Leveraging Artificial Intelligence for Digital Symptom Management in Oncology: The Development of CRCWeb.

Digital health interventions offer promise for scalable and accessible health care, but access is still limited by some participatory challenges, espe...

Nanotechnology-Enhanced siRNA Delivery: Revolutionizing Cancer Therapy.

RNA interference (RNAi) has emerged as a transformative approach for cancer therapy, enabling precise gene silencing through small interfering RNA (si...

Unsupervised risk factor identification across cancer types and data modalities via explainable artificial intelligence

Risk stratification is a key tool in clinical decision-making, yet current approaches often fail to translate sophisticated survival analysis into a...

Predicting Genetic Mutations from Single-Cell Bone Marrow Images in Acute Myeloid Leukemia Using Noise-Robust Deep Learning Models

In this study, we propose a robust methodology for identification of myeloid blasts followed by prediction of genetic mutation in single-cell images...

Unleashing Diffusion and State Space Models for Medical Image Segmentation

Existing segmentation models trained on a single medical imaging dataset often lack robustness when encountering unseen organs or tumors. Developing...

Characterization of m6A-Related Genes in Tumor-Associated Macrophages for Prognosis, Immunotherapy, and Drug Prediction in Lung Adenocarcinomas Based on Machine Learning Algorithms.

Tumor-associated macrophages (TAMs) are a vital immune component within the tumor microenvironment (TME) of lung adenocarcinoma (LUAD), exerting signi...

Hierarchical Deep Feature Fusion and Ensemble Learning for Enhanced Brain Tumor MRI Classification

Accurate brain tumor classification is crucial in medical imaging to ensure reliable diagnosis and effective treatment planning. This study introduc...