Artificial Intelligence Medical Compendium

Ovarian cancer (OC), predominantly epithelial OC, remains the most lethal gynecological malignancy. Owing to its often asymptomatic or non-specific clinical presentation, approximately 70 % of patients are diagnosed at advanced stages (FIGO III-IV), ... read more 

The cotton sector has recently encountered various obstacles, and traditional methods persist in the identification of cotton leaf diseases. This study has established an automated approach for diagnosing cotton leaf blast disease via deep learning m... read more 

BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE patients is significantly increased, and the cancer is often diagnosed at an advanced stage. Early s... read more 

Endometriosis (EM) affects approximately 10% of women of reproductive age and remains a prevalent estrogen-dependent gynecological disorder with limited therapeutic efficacy and high recurrence rates. Ferroptosis-an iron-dependent, non-apoptotic form... read more 

BACKGROUND: Although mindfulness ecological momentary interventions (MEMI) appear effective in alleviating worry symptoms, treatment engagement remains suboptimal. Determining baseline variables of MEMI over self-monitoring placebo (SM) can inform ta... read more 

BACKGROUND AND OBJECTIVE: Only a limited number of explainable artificial intelligence (XAI) models have been developed for the functional near-infrared spectroscopy (fNIRS)-based computer-aided diagnosis (CAD) of major depressive disorder (MDD). In ... read more 

OBJECTIVE: This study aims to develop and validate an interpretable prediction model for recognizing depression risk in primary and secondary school students based on acoustic features of speech using multiple machine learning methods. METHODS: This ... read more 

OBJECTIVE: With college freshmen under increasing psychological pressures, early detection of those at risk is critical. We applied machine learning to predict their mental health risks. METHODS: A psychological screening using UPI and SDS scales was... read more 

OBJECTIVES: Non-suicidal self-injury (NSSI) is a strong predictor and a gateway to suicide attempts (SA) among youth. Therefore, understanding how individuals with NSSI develop thoughts of SA is crucial for early prevention. This study aims to analyz... read more 

BACKGROUND: The emergence of novel psychoactive substances (NPSs) has overwhelmed forensic, health care, and regulatory systems. Conventional analytical techniques are ineffective for identifying known compounds but fail against newly synthesized NPS... read more