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Latest AI and machine learning research in prescriptions for healthcare professionals.

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Multi-target meridians classification based on the topological structure of anti-cancer phytochemicals using deep learning.

ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese medicine (TCM) meridian is the key theoretical g...

Artificial intelligence in small molecule drug discovery from 2018 to 2023: Does it really work?

Utilizing artificial intelligence (AI) in drug design represents an advanced approach for identifyin...

Revolutionizing drug formulation development: The increasing impact of machine learning.

Over the past few years, the adoption of machine learning (ML) techniques has rapidly expanded acros...

MM-GANN-DDI: Multimodal Graph-Agnostic Neural Networks for Predicting Drug-Drug Interaction Events.

Personalized treatment of complex diseases relies on combined medication. However, the occurrence of...

Artificial Intelligence for Drug Discovery: Are We There Yet?

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial i...

Using ChatGPT to predict the future of personalized medicine.

Personalized medicine is a novel frontier in health care that is based on each person's unique genet...

Deep learning driven de novo drug design based on gastric proton pump structures.

Existing drugs often suffer in their effectiveness due to detrimental side effects, low binding affi...

Effect of real-time oxygen consumption versus fixed flow-based low flow anesthesia on oxygenation and perfusion: a randomized, single-blind study.

Although low-flow anesthesia is widely used due to its various advantages, there are concerns about ...

Dental implant brand and angle identification using deep neural networks.

STATEMENT OF PROBLEM: Determining the brand and angle of an implant clinically or radiographically c...

Artificial intelligence revolutionizing drug development: Exploring opportunities and challenges.

By harnessing artificial intelligence (AI) algorithms and machine learning techniques, the entire dr...

Deep learning based source imaging provides strong sublobar localization of epileptogenic zone from MEG interictal spikes.

Electromagnetic source imaging (ESI) offers unique capability of imaging brain dynamics for studying...

First fully-automated AI/ML virtual screening cascade implemented at a drug discovery centre in Africa.

Streamlined data-driven drug discovery remains challenging, especially in resource-limited settings....

Artificial intelligence-enhanced electrocardiography for early assessment of coronavirus disease 2019 severity.

Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocardiography...

DAHNGC: A Graph Convolution Model for Drug-Disease Association Prediction by Using Heterogeneous Network.

In the field of drug development and repositioning, the prediction of drug-disease associations is a...

Artificial intelligence for natural product drug discovery.

Developments in computational omics technologies have provided new means to access the hidden divers...

An improved multi-modal representation-learning model based on fusion networks for property prediction in drug discovery.

Accurate characterization of molecular representations plays an important role in the property predi...

Combining SILCS and Artificial Intelligence for High-Throughput Prediction of the Passive Permeability of Drug Molecules.

Membrane permeability of drug molecules plays a significant role in the development of new therapeut...

Determinants of Attitude to a Humanoid Social Robot in Care for Older Adults: A Post-Interaction Study.

BACKGROUND While there is a growing body of research examining opinions on social robots in elderly ...

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chem...

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