AIMC Topic: Humans

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ERNIE-ac4C: A Novel Deep Learning Model for Effectively Predicting N4-acetylcytidine Sites.

Journal of molecular biology
RNA modifications are known to play a critical role in gene regulation and cellular processes. Specifically, N4-acetylcytidine (ac4C) modification has emerged as a significant marker involved in mRNA translation efficiency, stability, and various dis...

DOGpred: A Novel Deep Learning Framework for Accurate Identification of Human O-linked Threonine Glycosylation Sites.

Journal of molecular biology
O-linked glycosylation is a crucial post-translational modification that regulates protein function and biological processes. Dysregulation of this process is associated with various diseases, underscoring the need to accurately identify O-linked gly...

Deep learning assisted prediction of osteogenic capability of orthopedic implant surfaces based on early cell morphology.

Acta biomaterialia
The surface modification of titanium (Ti) and its alloys is crucial for improving their osteogenic capability, as their bio-inert nature limits effective osseointegration despite their prevalent use in orthopedic implants. However, these modification...

Regulatory approaches towards AI Medical Devices: A comparative study of the United States, the European Union and China.

Health policy (Amsterdam, Netherlands)
The swift progression of AI within the realm of medical devices has precipitated an imperative for stringent regulatory oversight. The United States, the European Union, and China stand as vanguard entities in the regulatory landscape for AI-enhanced...

Practical X-ray gastric cancer diagnostic support using refined stochastic data augmentation and hard boundary box training.

Artificial intelligence in medicine
Endoscopy is widely used to diagnose gastric cancer and has a high diagnostic performance, but it must be performed by a physician, which limits the number of people who can be diagnosed. In contrast, gastric X-rays can be taken by radiographers, thu...

A Cross-Sectional Survey of Optometrists in Canada Regarding Referral Patterns and a Needs Assessment for an Artificial Intelligence Referral Screening Tool for Epiretinal Membrane.

Ophthalmic surgery, lasers & imaging retina
BACKGROUND AND OBJECTIVE: This study evaluated optometrists' referral patterns for epiretinal membrane (ERM) patients in Ontario, Canada, and their attitudes towards an artificial intelligence (AI) tool for improving referral accuracy. An anonymous o...

Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak.

Artificial intelligence in medicine
BACKGROUND: Controlling re-emerging outbreaks such as COVID-19 is a critical concern to global health. Disease forecasting solutions are extremely beneficial to public health emergency management. This work aims to design and deploy a framework for r...

ABIET: An explainable transformer for identifying functional groups in biological active molecules.

Computers in biology and medicine
Recent advancements in deep learning have revolutionized the field of drug discovery, with Transformer-based models emerging as powerful tools for molecular design and property prediction. However, the lack of explainability in such models remains a ...

Temporal pavlovian conditioning of a model spiking neural network for discrimination sequences of short time intervals.

Journal of computational neuroscience
The brain's ability to learn and distinguish rapid sequences of events is essential for timing-dependent tasks, such as those in sports and music. However, the mechanisms underlying this ability remain an active area of research. Here, we present a P...