Cardiovascular

Artificial neural network analysis for oxytactic microbes in hybrid nanofluid with chemical reaction and thermal radiation.

The purpose of this investigation is to assess the outcome of Oxytactic microorganism in chemical reactive flow of TiO2 + GO/water based hybrid nanofluid flow across a sheet applying artificial intelligence. [Formula: see text] and [Formula: see text] nanoparticles are combined with the base fluid, water ([Formula: see text]). There are numerous real-world uses for the concept of artificial intell...

Prediction of OncotypeDX recurrence score using hematoxylin and eosin-stained whole slide images.

The OncotypeDX 21-gene assay guides adjuvant chemotherapy decisions in early-stage, hormone receptor-positive, HER2-negative breast cancer, but cost and turnaround time limit access. This study presents a deep learning-based approach for predicting OncotypeDX recurrence scores directly from hematoxylin and eosin-stained whole slide images. Our approach leverages a deep learning foundation model pr...

Comparative oncology of male and female breast cancer: diagnostic paradigms and machine learning approaches in treatment.

Breast cancer is associated mostly with women; however, breast cancer also appears in men, which dictates the need to know about gender-specific diffe...

Artificial Intelligence in Breast Cancer Lymph Node Evaluation: Is Neoadjuvant Chemotherapy the Achilles' Heel?

CONTEXT.—: Artificial intelligence (AI) has demonstrated high accuracy in detecting lymph node (LN) metastases in treatment-naïve invasive breast canc...

Precision theranostics in oncology: integrating antibody-drug conjugates, radioimmunotherapy, and immuno‑PET for adaptive cancer care.

The century-old vision of a "magic bullet" in oncology is being realized through the paradigm of precision theranostics, which formally integrates tar...

Integrating machine learning and single-cell sequencing to reveal the role of kinase-related genes in subtype classification and prognostic significance of lung squamous cell carcinoma.

BACKGROUND: Lung squamous cell carcinoma (LUSC) exhibits poor prognosis and a highly complex tumor immune microenvironment (TIME), creating an urgent ...

Feasibility of retrieval-augmented generation for large language models with Japanese input in radiotherapy.

Large language models (LLMs) have recently gained attention for their potential. However, concerns remain regarding their reliability due to limitatio...

Exploring the prognostic role of senescence-related genes in gastric cancer through multi-omics integration and machine learning.

Cellular senescence plays a context-dependent role in gastric cancer (GC), functioning both through tumor-suppressive arrest and the tumor-promoting s...

Development of Models for Predicting the 7-Month Risk of Venous Thromboembolism and Clinically Relevant Bleeding in Ambulatory Patients with Cancer: Analysis from the AVERT Trial.

BACKGROUND: Patients with cancer are at elevated risk of venous thromboembolism (VTE). While primary thromboprophylaxis reduces VTE incidence, it also...

Artificial intelligence, omics, and biomarkers: Redefining lung cancer early detection.

Lung cancer, the leading cause of death worldwide, claims millions of lives yearly, largely due to limited early interventions. Currently used lung ca...

AI-predicted spatial transcriptomics unlocks breast cancer biomarkers from pathology.

Spatial transcriptomics (ST) assays are transforming our understanding of tumor heterogeneity, but their high cost limits their application in large-s...

Machine learning-based integration of transcriptome and digital pathology for predicting chemoresistance in muscle-invasive bladder cancer.

Muscle-invasive bladder cancer (MIBC) presents with variable clinical and pathological features, leading to inconsistent responses to standard treatme...

De novo and scaffold-based design of GDF15 binders for cancer cachexia diagnostics and therapeutics.

Growth differentiation factor-15 (GDF15), a stress-responsive cytokine of the transforming growth factor-β superfamily, is elevated in cancer cachexia...

ELOVL1 promotes the progression of intrahepatic cholangiocarcinoma by enhancing endoplasmic reticulum stress and the PI3K/AKT/mTOR signaling pathway.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is a highly aggressive liver malignancy characterized by an adverse outcome attributed to delayed d...

Emerging Therapeutic Paradigms in Tuberculosis: Nanocarriers, Host-Directed Strategies, and Translational Pharmacology.

TB remains a significant global health burden due to protracted therapeutic courses, poor patient compliance, and toxicities associated with drug trea...

Managing multidrug resistant Gram-negative bacteraemia in immunocompromised hosts.

PURPOSE OF REVIEW: Multidrug-resistant Gram-negative bloodstream infections (MDR-GNBSI) are increasingly frequent in immunocompromised hosts, particul...

Reconstruction algorithms and arm positioning effects on abdominal CT image quality and radiation dose: a phantom study.

OBJECTIVE: To evaluate the effects of arm positioning and reconstruction algorithms on radiation dose and image quality of abdominal CT. MATERIALS AND...

Pancreatic cancer.

Pancreatic ductal adenocarcinoma remains one of the deadliest malignancies, characterized by late diagnosis, aggressive biology and limited therapeuti...

An interpretable deep learning biomarker for prognostication and prediction of adjuvant chemotherapy benefit in gastric cancer.

Prognostic stratification in gastric cancer (GC) currently relies on the tumour-node-metastasis (TNM) staging system, which incompletely captures tumo...

Machine learning enhanced optical spectroscopy for breast cancer diagnosis: A review.

This literature review examines the transformative role of machine learning (ML) and deep learning (DL) in enhancing optical spectroscopy for breast c...