Artificial Intelligence Medical Compendium

Pesticides are suspected to cause health effects in humans, but human-based data on their toxicity are often insufficient to establish associations and quantify risks. We reviewed literature on trichlorfon and investigated methodological aspects of r... read more 

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INTRODUCTION: Gastric cancer remains a major global health burden, with high mortality driven by late-stage diagnoses that limit treatment options and reduce survival. Current diagnostic methods such as endoscopy and biopsy are invasive, resource-int... read more 

ETHNOPHARMACOLOGICAL RELEVANCE: Gelsemium elegans Benth. (G. elegans) is a highly toxic medicinal plant traditionally used to treat pain and inflammatory disorders. Accidental ingestion or misuse often causes severe poisoning and death, primarily due... read more 

Exosomes are small, membrane-enclosed vesicles that can originate from a variety of sources and contain a wealth of material. They are involved in physiological processes such as cell-cell communication, cell migration, and anti-tumor immunity, and a... read more 

With growing interest in microneedle technology for enhancing transdermal drug delivery, the current body of literature provides a valuable data reservoir for understanding and predicting mechanical performance - a critical prerequisite for microneed... read more 

OBJECTIVE: The purpose of this study was to develop a lightweight multimodal deep learning model for accurately predicting the risk of postoperative vitreous cavity haemorrhage (POVCH) following vitrectomy with intraocular pharmacotherapy in patients... read more 

INTRODUCTION: Blood-based biomarkers that can aid diagnosis of Parkinson's Disease (PD) dementia (PDD), and predict PDD onset in people with PD are urgently needed. Plasma small extracellular vesicles (SEV) reflect molecular changes in living human b... read more 

OBJECTIVE: To develop and validate a machine learning model for postoperative sepsis in critically ill traumatic spinal injury (TSI) patients, a frequent and severe complication without dedicated predictive tools. METHODS: Model development used the ... read more 

Considering the inherent multi-scale nature of solar irradiance data is essential for accurate long-term forecasting. However, when temporal dynamics at multiple scales are represented in 1D space, critical time dependencies become deeply obscured, m... read more