AIMC Topic: Male

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A novel potential biomarker panel to diagnose depression derived from big proteomic data.

Journal of affective disorders
BACKGROUND: There is still no clinical biomarker to diagnose depression. Given the complexity of a multifactorial disease like depression, a single biomarker is unlikely to capture the full heterogeneity of the disease and be applicable in clinical p...

Understanding the relationship between rosemary odor and mental workload through deep learning.

Neuroscience
This research explores the novel application of aromatic odors, specifically rosemary, in reducing mental workload, employing deep learning methods to analyze electroencephalogram (EEG) signals without feature extraction. Thirty volunteers participat...

A machine learning-based predictive model for multilobar pulmonary consolidation induced by macrolide-resistant pneumonia caused by the 23S rRNA A2063G mutation.

Microbiology spectrum
This study aims to develop a machine learning (ML)-based predictive model for assessing the risk of multilobar pulmonary consolidation in children with macrolide-resistant pneumonia (MRMP) caused by the 23S rRNA A2063G mutation, a subgroup underrepr...

Developing an explainable machine learning model to predict false-negative citrin deficiency cases in newborn screening.

Orphanet journal of rare diseases
BACKGROUND: Neonatal Intrahepatic Cholestasis caused by Citrin Deficiency (NICCD) is an autosomal recessive disorder affecting the urea cycle and energy metabolism. Newborn screening (NBS) usually relies on elevated citrulline, but some patients have...

Artificial intelligence-assisted endoscopic diagnosis system for diagnosing Helicobacter pylori infection: a multicenter study.

BMC medicine
BACKGROUND: Deep learning algorithm-based artificial intelligence (AI) has significantly advanced the domain of endoscopic diagnosis; however, its utilization for detecting Helicobacter pylori (H. pylori) infections remains constrained. We aimed to d...

The value of cardiac CT based inflammatory risk assessment in predicting cardiovascular events: a case report.

BMC cardiovascular disorders
BACKGROUND: Vascular inflammation plays a critical role in the development of coronary artery disease (CAD). Measurement of coronary inflammation from coronary computed tomography angiography (CCTA) using the perivascular fat attenuation index (FAI) ...

Development and validation of an age estimation model based on dental characteristics using panoramic radiographs.

Scientific reports
Dental characteristics have considerable potential as indicators for estimating chronological age. This study developed a regression model for age estimation using dental characteristics observed in panoramic radiographs. A total of 2,391 radiographs...

ACXNet hybrid deep learning model for cross task mental workload estimation using EEG neural manifolds.

Scientific reports
Mental workload is an interdisciplinary construct that significantly influences human performance, particularly in tasks requiring sustained attention and cognitive processing. Effective mental workload assessment is critical for preventing cognitive...

A machine learning approach for detection of claustrophobic brain activity in electroencephalography.

Scientific reports
Claustrophobia, a phobia with a specific unreasonable and excessive fear of enclosed spaces, can have a considerable impact on an individual's life. Electroencephalography (EEG) has been a tool with potential for studying neural processes in anxiety ...