AIMC Topic: Female

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An Artificial Intelligence Olfactory-Based Diagnostic Model for Parkinson's Disease Using Volatile Organic Compounds from Ear Canal Secretions.

Analytical chemistry
Parkinson's Disease (PD), a frequently diagnosed neurodegenerative condition, poses a major global challenge. Early diagnosis and intervention are crucial for PD treatment. This study proposes a diagnostic model for PD that analyzes volatile organic ...

Contrastive functional connectivity defines neurophysiology-informed symptom dimensions in major depression.

Cell reports. Medicine
Major depressive disorder (MDD) is highly heterogeneous, posing challenges for effective treatment due to complex interactions between clinical symptoms and neurobiological features. To address this, we apply contrastive principal-component analysis ...

An integrated analytical approach for biomarker discovery in esophageal cancer: Combining trace element and oxidative stress profiling with machine learning.

Journal of trace elements in medicine and biology : organ of the Society for Minerals and Trace Elements (GMS)
BACKGROUND: Early detection of esophageal squamous cell carcinoma (ESCC) significantly improves survival rates, yet reliable biochemical biomarkers for early diagnosis remain limited. The aim of this study is to identify potential early diagnostic bi...

Deep learning for predicting invasive recurrence of ductal carcinoma in situ: leveraging histopathology images and clinical features.

EBioMedicine
BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to ipsilateral invasive breast cancer (IBC) but over 75% of DCIS lesions do not progress if untreated. Currently, DCIS that might progress to IBC cannot reliably be identified. Therefore, most ...

Detecting Tardive Dyskinesia Using Video-Based Artificial Intelligence.

The Journal of clinical psychiatry
Tardive dyskinesia (TD) is a late-onset adverse effect of dopamine receptor-blocking medications, characterized by involuntary movements primarily affecting the mouth, though other body parts may be involved. Severity of TD varies from mild to debil...

Operationalizing postmortem pathology-MRI association studies in Alzheimer's disease and related disorders with MRI-guided histology sampling.

Acta neuropathologica communications
Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling that may miss critical areas affected by Alzheimer's disease and related disorders. Ultra-high reso...

Comparing orthodontic pre-treatment information provided by large language models.

BMC oral health
This study collected and screened the 50 most common pre-treatment consultation questions from adult orthodontic patients through clinical practice. Responses to these questions were generated using three large language models: Ernie Bot, ChatGPT, an...

Performance of a novel multimodal large language model in ınterpreting meibomian glands quantitatively and qualitatively.

International ophthalmology
PURPOSE: To evaluate the performance of a multimodal large language model (LLM), Claude 3.5 Sonnet, in interpreting meibography images for Meibomian gland dropout grading and morphological abnormality detection.

Personalized prediction of gait freezing using dynamic mode decomposition.

Scientific reports
Freezing of gait (FoG) is a common severe gait disorder in patients with advanced Parkinson's disease. The ability to predict the onset of FoG episodes early on allows for timely intervention, which is essential for improving the life quality of pati...

Improving ACS prediction in T2DM patients by addressing false records in electronic medical records using propensity score.

Scientific reports
Our study aims to improve the prediction performance of machine learning (ML) models by addressing false records (i.e., false positive, false negative, or missingness) in binary categorical variables in electronic medical records (EMRs) using propens...