AIMC Topic: Middle Aged

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Large medical image database impact on generalizability of synthetic CT scan generation.

Computers in biology and medicine
This study systematically examines the impact of training database size and the generalizability of deep learning models for synthetic medical image generation. Specifically, we employ a Cycle-Consistency Generative Adversarial Network (CycleGAN) wit...

A machine learning framework for cross-institute standardized analysis of flow cytometry in differentiating acute myeloid leukemia from non-neoplastic conditions.

Computers in biology and medicine
Flow cytometry (FC) remains a cornerstone diagnostic tool for acute myeloid leukemia (AML), yet standardizing panels across laboratories presents persistent challenges. Our study introduces a validated machine learning framework enabling cross-panel ...

Activity recognition in patients with tremor: Integrating time-length windows for enhanced detection.

Computers in biology and medicine
Pathological tremor significantly impairs daily activities and quality of life, particularly in conditions such as essential tremor and Parkinson's disease. The assessment and evaluation of tremor, along with its evolution with medication dosages, po...

Distinct processing stages of cross-modal conflict in schizophrenia: The role of auditory cortex underactivation.

Schizophrenia research
BACKGROUND: The cross-modal conflict deficit is a key feature of schizophrenia. However, it remains largely unknown whether cross-modal conflict in schizophrenia diverges at distinct processing stages and its potential association with the auditory c...

Volatomics for Diagnosis and Risk Stratification of MASLD: A Proof-Of-Concept Study.

Alimentary pharmacology & therapeutics
BACKGROUND AND AIMS: Human breath contains numerous volatile organic compounds (VOCs) produced by physiological and metabolic processes or perturbed in pathological states. Electronic nose (eNose) technology has been extensively validated as a non-in...

A Minimal Annotation Pipeline for Deep Learning Segmentation of Skeletal Muscles.

NMR in biomedicine
Translating quantitative skeletal muscle MRI biomarkers into clinics requires efficient automatic segmentation methods. The purpose of this work is to investigate a simple yet effective iterative methodology for building a high-quality automatic segm...

The implementation of artificial intelligence in serial monitoring of post gamma knife vestibular schwannomas: A pilot study.

Clinical imaging
BACKGROUND: Vestibular schwannomas (VS) are benign tumors that can lead to hearing loss, balance issues, and tinnitus. Gamma Knife Radiosurgery (GKS) is a common treatment for VS, aimed at halting tumor growth and preserving neurological function. Ac...

AI-powered speech device as a tool for neuropsychological assessment of an older adult population: A preliminary study.

Acta psychologica
As the older adult population continues to expand, the demands on the healthcare system intensifies, necessitating the development of technologies that effectively accommodate the requirements of older adults. While Artificial Intelligence (AI) syste...

Machine learning prediction of pathological complete response to neoadjuvant chemotherapy with peritumoral breast tumor ultrasound radiomics: compare with intratumoral radiomics and clinicopathologic predictors.

Breast cancer research and treatment
PURPOSE: Noninvasive, accurate and novel approaches to predict patients who will achieve pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) could assist treatment strategies. The aim of this study was to explore the application...