Oncology/Hematology

A deep learning-based framework for patient-specific radiation dose prediction in beta-emitting radionuclide therapies.

OBJECTIVE: Conventional image-based models for radionuclide therapy dosimetry are typically radionuclide-specific and rely on nuclear medicine (NM) images for training. We developed a deep learning (DL) model that predicts doses for not only training radionuclides but also radionuclides not included in the training data without patient NM images. APPROACH: The DL model was trained to predict voxel...

Minimally invasive spine surgery: current advantages, limitations, and future directions.

Minimally invasive spine surgery (MISS), supported by advancements in endoscopic systems, tubular retractors, lateral access corridors, image-guided navigation, and robotic assistance, has progressively expanded its role in the management of a broad spectrum of spinal disorders. These approaches were developed to limit muscular disruption and soft tissue damage while maintaining clinical and radio...

Comparison of Left Ventricular Ejection Fraction Among 18F-FDG Dual-Gated PET/CT, Single-Gated PET/MRI, and Cardiac MRI.

Left ventricular ejection fraction (LVEF) is a critical parameter in the evaluation of cardiac function, and its measurement can guide treatment decis...

Patient Perceptions of Artificial Intelligence in Orthopaedic Surgery: Identifying Potential Barriers to Acceptance and Disparities With Implementation.

INTRODUCTION: Despite growing enthusiasm for artificial intelligence (AI) implementation in orthopaedic care, patient attitudes toward AI adoption rem...

Enhancing cancer drug discovery: QSAR modeling with machine learning and chemical representations.

Accurately predicting the bioactivity of small molecules against cancer therapeutic targets remains a significant challenge at the intersection of che...

Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases.

OBJECTIVE: To construct and interpret a machine learning model for predicting overall survival in nonsurgical prostate cancer with bone metastases (PC...

Ganglioside-Mediated Neural-Acinar Crosstalk Facilitates Pancreatic Carcinogenesis via Metaplastic Niche Remodeling.

BACKGROUND & AIMS: Neural networks constitute a crucial component of the tumor microenvironment that remains underexplored in pancreatic carcinogenesi...

Composite pathway-guided Cox modeling for interpretable survival prediction in breast cancer.

Accurate survival prediction in breast cancer is essential for patient risk stratification and personalized treatment planning. Although transcriptomi...

Twisted Tapestry of Tumors: Updates in Molecular Pathology of Breast Tumors.

This article explores the expanding role of molecular diagnostics in breast pathology. It emphasizes how immunohistochemistry, fluorescence in situ hy...

Are large language models consistent with the ASPS and AAPS guidelines? A comparison of AI chatbot recommendations and plastic surgery clinical guidance.

INTRODUCTION: Assessing the ability of AI chatbots to provide information consistent with clinical guidelines is essential for evaluating the accuracy...

Peritumoral habitat radiomics predicts axillary lymph node metastasis in breast cancer.

Accurate preoperative prediction of axillary lymph node metastasis (ALNM) is critical for personalized management of breast cancer. Here, we developed...

Anharmonic Thermodynamics Redefines Metastability and Parent Phases in Ferroelectric HfO2.

Hafnia (HfO2) is a silicon-compatible dielectric material, yet stabilizing its desired but metastable ferroelectric phase remains challenging. Phase s...

Robust Histopathology Subtyping via Perturbation Fidelity in Deep Classifier.

Deep learning for invasive lung adenocarcinoma subtyping remains vulnerable to real-world imaging perturbations. We present a margin consistency frame...

Combining computed tomography radiomics and clinical features to predict lymph node metastasis in patients with lung cancer.

BACKGROUND: Accurate preoperative assessment of lymph node metastasis (LNM) is crucial for treatment planning and prognostic stratification in patient...

scCAPReSE: detection of large-scale genomic rearrangements from single-cell Hi-C based on few-shot learning.

Large-scale genomic rearrangements are prevalent in cancer genomes and can profoundly rewire three-dimensional (3D) genome architecture, leading to ab...

Comprehensive Multiomics Characterization of Perineural Invasion in Cervical Cancer Reveals Diagnostic Markers, Molecular Drivers, and Therapeutic Strategies.

UNLABELLED: Perineural invasion (PNI) is an important pathologic feature of cervical cancer that is associated with poor prognosis and provides key in...

Discovery of Novel MLKL PROTAC Degraders for the Treatment of Hepatocellular Carcinoma via Promoting Parthanatos.

Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, primarily due to its low immunogenicity and immunosuppre...

Machine learning models based on MRI predict the expression levels of Galectin - 9 expression in rectal cancer.

OBJECTIVE: To investigate the utility of a machine learning model based on MRI radiomics in predicting the expression of Galectin-9 in rectal cancer. ...

Predicting intrahepatic recurrence of colorectal cancer liver metastases after curative hepatectomy using a machine learning model with data integration of ultrasound radiomics and clinicopathological parameters.

OBJECTIVES: To develop and validate a machine learning model integrating ultrasound radiomics and clinicopathological parameters to predict intrahepat...

An integrated microfluidic system for automatic and self-validated analysis of cervical extracellular vesicle markers PD-L1 and ERBB3.

The early and precise diagnosis of gynecological malignancies, such as cervical cancer, is critical for improving patient treatments. Extracellular ve...