AIMC Topic: Middle Aged

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Prediction of the short-term efficacy and recurrence of photodynamic therapy in the treatment of oral leukoplakia based on deep learning.

Photodiagnosis and photodynamic therapy
BACKGROUND: The treatment of oral leukoplakia (OLK) with aminolaevulinic acid photodynamic therapy (ALA-PDT) is widespread. Nonetheless, there is variation in efficacy. Therefore, this study constructed a model for predicting the short-term efficacy ...

Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry.

NeuroImage
The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medi...

Prediagnosis recognition of acute ischemic stroke by artificial intelligence from facial images.

Aging cell
Stroke is a major threat to life and health in modern society, especially in the aging population. Stroke may cause sudden death or severe sequela-like hemiplegia. Although computed tomography (CT) and magnetic resonance imaging (MRI) are standard di...

Machine learning thermal comfort prediction models based on occupant demographic characteristics.

Journal of thermal biology
This study aims to investigate the predictive occupant demographic characteristics of thermal sensation (TS) and thermal satisfaction (TSa) as well as to find the most effective machine learning (ML) algorithms for predicting TS and TSa. To achieve t...

Deep learning models for thyroid nodules diagnosis of fine-needle aspiration biopsy: a retrospective, prospective, multicentre study in China.

The Lancet. Digital health
BACKGROUND: Accurately distinguishing between malignant and benign thyroid nodules through fine-needle aspiration cytopathology is crucial for appropriate therapeutic intervention. However, cytopathologic diagnosis is time consuming and hindered by t...

Causal Forest Machine Learning Analysis of Parkinson's Disease in Resting-State Functional Magnetic Resonance Imaging.

Tomography (Ann Arbor, Mich.)
In recent years, Artificial Intelligence has been used to assist healthcare professionals in detecting and diagnosing neurodegenerative diseases. In this study, we propose a methodology to analyze functional Magnetic Resonance Imaging signals and per...

Ultrasound contrast-enhanced radiomics model for preoperative prediction of the tumor grade of clear cell renal cell carcinoma: an exploratory study.

BMC medical imaging
BACKGROUND: This study aims to explore machine learning(ML) methods for non-invasive assessment of WHO/ISUP nuclear grading in clear cell renal cell carcinoma(ccRCC) using contrast-enhanced ultrasound(CEUS) radiomics.

Exploring the relationship between heavy metals and diabetic retinopathy: a machine learning modeling approach.

Scientific reports
Diabetic retinopathy (DR) is one of the leading causes of adult blindness in the United States. Although studies applying traditional statistical methods have revealed that heavy metals may be essential environmental risk factors for diabetic retinop...

Spectro-temporal acoustical markers differentiate speech from song across cultures.

Nature communications
Humans produce two forms of cognitively complex vocalizations: speech and song. It is debated whether these differ based primarily on culturally specific, learned features, or if acoustical features can reliably distinguish them. We study the spectro...

Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study.

EBioMedicine
BACKGROUND: Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. However, colorectal cancers in contrast-enhanced CT without bowel preparation may elude detection by radiologists. We aimed to develop a deep learning (DL...