AIMC Topic: Aged

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Convolutional neural network for classifying primary liver cancer based on triple-phase CT and tumor marker information: a pilot study.

Japanese journal of radiology
PURPOSE: To develop convolutional neural network (CNN) models for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) and predicting histopathological grade of HCC.

Accurate prediction of acute pancreatitis severity with integrative blood molecular measurements.

Aging
BACKGROUND: Early diagnosis of severe acute pancreatitis (SAP) is essential to minimize its mortality and improve prognosis. We aimed to develop an accurate and applicable machine learning predictive model based on routine clinical testing results fo...

A new rapid diagnostic system with ambient mass spectrometry and machine learning for colorectal liver metastasis.

BMC cancer
BACKGROUND: Probe electrospray ionization-mass spectrometry (PESI-MS) can rapidly visualize mass spectra of small, surgically obtained tissue samples, and is a promising novel diagnostic tool when combined with machine learning which discriminates ma...

Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model.

Radiology
Background Missing MRI sequences represent an obstacle in the development and use of deep learning (DL) models that require multiple inputs. Purpose To determine if synthesizing brain MRI scans using generative adversarial networks (GANs) allows for ...

Machine Learning and Novel Biomarkers for the Diagnosis of Alzheimer's Disease.

International journal of molecular sciences
BACKGROUND: Alzheimer's disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on cognitive tests, imaging techniques and cerebrospinal fluid (CSF) lev...

A new machine learning approach for predicting likelihood of recurrence following ablation for atrial fibrillation from CT.

BMC medical imaging
OBJECTIVE: To investigate left atrial shape differences on CT scans of atrial fibrillation (AF) patients with (AF+) versus without (AF-) post-ablation recurrence and whether these shape differences predict AF recurrence.

Machine learning models to identify low adherence to influenza vaccination among Korean adults with cardiovascular disease.

BMC cardiovascular disorders
BACKGROUND: Annual influenza vaccination is an important public health measure to prevent influenza infections and is strongly recommended for cardiovascular disease (CVD) patients, especially in the current coronavirus disease 2019 (COVID-19) pandem...

Novel "Modified Bascule Method" for Lymphadenectomy Along the Left Recurrent Laryngeal Nerve During Robot-Assisted Minimally Invasive Esophagectomy.

Annals of surgical oncology
BACKGROUND: Given the worldwide popularization of conventional minimally invasive esophagectomy (C-MIE), robot-assisted MIE (RAMIE) can be expected to provide a finer procedure. However, controversy remains regarding whether RAMIE is superior to C-MI...

Prediction of Drug-Induced Long QT Syndrome Using Machine Learning Applied to Harmonized Electronic Health Record Data.

Journal of cardiovascular pharmacology and therapeutics
BACKGROUND: Drug-induced QT prolongation is a potentially preventable cause of morbidity and mortality, however there are no widespread clinical tools utilized to predict which individuals are at greatest risk. Machine learning (ML) algorithms may pr...