Oncology/Hematology

Artificial Intelligence in Adolescent and Young Adult Cancer Care: A Discussion Paper.

PURPOSE: The number of adolescents and young adults (AYAs) with cancer has increased over the past 30 years. Fundamental to this process has been the combined contribution from nursing and other health care professionals. METHODS: The authors discuss artificial intelligence (AI) and digital technologies to support the care of AYAs with cancer in the United Kingdom. Two innovative projects are high...

Chemotherapy-Sparing Strategies in Follicular Lymphoma: Emerging Targeted and Immune-Based Approaches.

Follicular lymphoma (FL), traditionally considered an indolent yet incurable malignancy, is experiencing a substantial evolution in its therapeutic landscape with the emergence of chemo-free treatment strategies. These novel approaches challenge conventional chemotherapy-based paradigms and offer promising alternatives for both newly diagnosed and relapsed/refractory (RR) FL patients. Among these ...

Causal Inference and Prognostic Modeling in Colorectal Cancer through Integration of Computational Pathology and Mendelian Randomization.

BACKGROUND: While traditional pathology supports the diagnosis and staging of colorectal cancer (CRC), computational pathology provides novel prognost...

Proteomic Profiling of Plasma Extracellular Vesicles Combined with Multivariate Modeling Identified Potential Biomarkers for Distinguishing Benign Pulmonary Nodules from Early-Stage Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer and is difficult to distinguish from benign pulmonary nodules (BPNs), particularl...

Ensemble learning-based radiomics model for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

PURPOSE: To develop and validate a multimodal ensemble machine learning model integrating multi-sequence magnetic resonance imaging (MRI) radiomics, c...

Augmented intelligence for multimodal virtual biopsy in breast cancer using generative artificial intelligence.

OBJECTIVE: This study aims to propose a multimodal, multi-view deep learning approach for breast cancer virtual biopsy, a non-invasive classification ...

HepatoAILFA: Machine-Learning-Assisted Nano-enhanced Point-of-Care System for Personalized Precise Diagnosis of Hepatocellular Carcinoma.

Early diagnosis significantly improves survival rates for hepatocellular carcinoma (HCC), yet traditional methods face limitations, including speciali...

Post-Translational Modification Mediated By Acylation Modification Related Genes Induces Immunosuppression and Immunotherapy Resistance in Head and Neck Squamous Cell Carcinoma.

Acylation modification plays a crucial role in modulating head and neck squamous cell carcinoma (HNSCC) progression, and their specific prognostic imp...

Computed Tomography-Pathology Deep Learning Model for the Precise Prediction of Recurrence in Pathological Stage IA Lung Adenocarcinoma.

BACKGROUND: The postoperative prognosis of pathological stage IA lung adenocarcinoma (LUAD) exhibits significant heterogeneity. While the tumor node m...

MGML: A plug-and-play meta-guided multi-modal learning framework for incomplete multimodal brain tumor segmentation.

Leveraging multimodal information from Magnetic Resonance Imaging (MRI) plays a vital role in lesion segmentation, especially for brain tumors. Howeve...

Combining the prognostic values of entropy-based heterogeneity features from 18 F-fluorodeoxyglucose PET and transmission computed tomography using machine learning in patients with lung adenocarcinoma undergoing curative surgery.

OBJECTIVE: The objective of this study is to evaluate the combined prognostic values of 18 F-fluorodeoxyglucose ( 18 F-FDG) PET and computed tomograph...

Recent Advances in Musculoskeletal Radiology: Bridging Innovation and Clinical Application.

Recent advances in musculoskeletal (MSK) radiology have markedly improved diagnostic accuracy through innovations in MRI, CT, and artificial intellige...

Development and external validation of an MRI radiomics-based machine learning model to predict tumour recurrence in brain metastases treated with Gamma Knife radiosurgery.

BACKGROUND: Predicting recurrence after gamma knife radiosurgery (GKRS) is clinically important, as it informs salvage treatment and patient managemen...

Subtype classification of gastric spindle cell tumors in whole slide images.

AIMS: Accurate cancer subtype classification is critical due to variations in tumor progression and prognosis. Traditionally, pathologists classified ...

Urinary Tumor DNA to Identify Candidates for Repeat Transurethral Resection in Non-Muscle-Invasive Bladder Cancer.

Repeat transurethral resection of bladder tumor (re-TURBT) is commonly recommended for patients with non-muscle-invasive bladder cancer (NMIBC) with h...

Preliminary Exploration of Discriminative Correlation Filter Network for Real-time Tracking of Inconspicuous Focal Liver Lesions on Conventional Ultrasound.

OBJECTIVE: This study aimed to explore the feasibility of a discriminative correlation filter network (DCFNet)-based algorithm for positioning inconsp...

A multicenter multimodel habitat radiomics model for predicting immunotherapy response in advanced NSCLC.

A robust predictive biomarker is critical for identifying patients with NSCLC who may benefit from immunotherapy. This study developed a CT-based habi...

Metal-based nanomaterials achieve tumor treatment strategies by overcoming the blood-brain barrier of glioma and responding to the tumor microenvironment.

Glioblastoma (GBM) continues to be the most lethal form of primary brain tumor. Therapeutic efficacy is significantly hindered by the presence of the ...

Intelligent theranostics all-in-one: Synergistic application of stimuli-responsive SERS nanoprobes for disease diagnosis and targeted therapy.

Surface-enhanced Raman scattering (SERS) technology, with its single-molecule detection capability and molecular specificity, has become a cornerstone...

Microrobots/micromotors in cancer therapeutics, advances and applications.

Cancer remains one of the most challenging diseases to conquer due to its high mortality rate and the lack of effective diagnostic and therapeutic too...