AIMC Topic: Aged

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Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data.

BMJ open
OBJECTIVES: To develop and validate a machine learning (ML) model to differentiate malignant from benign thyroid nodules (TNs) based on the routine data and provide diagnostic assistance for medical professionals.

Construction of exosome non-coding RNA feature for non-invasive, early detection of gastric cancer patients by machine learning: a multi-cohort study.

Gut
BACKGROUND AND OBJECTIVE: Gastric cancer (GC) remains a prevalent and preventable disease, yet accurate early diagnostic methods are lacking. Exosome non-coding RNAs (ncRNAs), a type of liquid biopsy, have emerged as promising diagnostic biomarkers f...

Optimizing Strategy for Lung Cancer Screening: From Risk Prediction to Clinical Decision Support.

JCO clinical cancer informatics
PURPOSE: Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality by detecting the disease at earlier, more treatable stages. However, high false-positive rates and the associated risks of subsequent invasive diagn...

Annotation-Free Whole-Slide Image Analysis Method to Assess Immune Infiltration in Colorectal Cancer.

JCO precision oncology
PURPOSE: Tumor-infiltrating lymphocytes (TILs) play a crucial role in host antitumor processes. High level of TILs is associated with better outcomes for patients. We aim to automatically quantify TILs without any nuclei annotation and further constr...

Explainable Machine Learning Models for Colorectal Cancer Prediction Using Clinical Laboratory Data.

Cancer control : journal of the Moffitt Cancer Center
IntroductionEarly diagnosis of colorectal cancer (CRC) poses a significant clinical challenge. This study aims to develop machine learning (ML) models for CRC risk prediction using clinical laboratory data.MethodsThis retrospective, single-center stu...

Machine Learning Models Can Predict Tinnitus and Noise-Induced Hearing Loss.

Ear and hearing
OBJECTIVES: Despite the extensive use of machine learning (ML) models in health sciences for outcome prediction and condition classification, their application in differentiating various types of auditory disorders remains limited. This study aimed t...

AgeML: Age Modeling With Machine Learning.

IEEE journal of biomedical and health informatics
An approach to age modeling involves the supervised prediction of age using machine learning from subject features. The derived age metrics are used to study the relationship between healthy and pathological aging in multiple body systems, as well as...

Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma From Multi-Sequence Magnetic Resonance Imaging Based on Deep Fusion Representation Learning.

IEEE journal of biomedical and health informatics
Recent studies have identified microvascular invasion (MVI) as the most vital independent biomarker associated with early tumor recurrence. With advancements in medical technology, several computational methods have been developed to predict preopera...

Interpretable Prognostic Modeling for Postoperative Pancreatic Cancer Using Multi-machine Learning and Habitat Radiomics: A Multi-center Study.

Academic radiology
RATIONALE AND OBJECTIVES: Accurate risk stratification is critical for guiding personalized treatment in resectable pancreatic cancer (RPC). This retrospective study assessed the utility of habitat radiomics for predicting recurrence-free survival (R...