ReviewStroke and vascular neurology2019
Artificial intelligence and big data facilitated targeted drug discovery.
Review in Stroke and vascular neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review on use of aminoquinolines for the therapeutic management of COVID-19: Efficacy, safety and clinical trials.Life sciences · 2020Pooled it
- Harnessing AI-driven reverse docking in drug discovery: a comprehensive review of opportunities, challenges, and emerging trends.Journal of molecular modeling · 2025Review
- Multimodal AI in Biomedicine: Pioneering the Future of Biomaterials, Diagnostics, and Personalized Healthcare.Nanomaterials (Basel, Switzerland) · 2025Review
- Applications of Artificial Intelligence in Drug Repurposing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Identification of anti-gastric cancer effects and molecular mechanisms of resveratrol: From network pharmacology and bioinformatics to experimental validation.World journal of gastrointestinal oncology · 2024Article
- Navigating the unseen peril: safeguarding medical imaging in the age of AI.Frontiers in artificial intelligence · 2024Review
- Molecular basis and pathways of the Yin-Yang theory in T cell immunity.Frontiers in immunology · 2024Article
- The future of medicine: an outline attempt using state-of-the-art business and scientific trends.Frontiers in medicine · 2024Review
- Discovery of an OTUD3 inhibitor for the treatment of non-small cell lung cancer.Cell death & disease · 2023Article
- Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system.Molecular diversity · 2023Review
- Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition.Sensors (Basel, Switzerland) · 2023Article
- Machine Learning and AI in Cancer Prognosis, Prediction, and Treatment Selection: A Critical Approach.Journal of multidisciplinary healthcare · 2023Review
- An automatic hypothesis generation for plausible linkage between xanthium and diabetes.Scientific reports · 2022Article
- Artificial intelligence in cancer target identification and drug discovery.Signal transduction and targeted therapy · 2022Review
- An overview of artificial intelligence in oncology.Future science OA · 2022Review
- Application of High Throughput Technologies in the Development of Acute Myeloid Leukemia Therapy: Challenges and Progress.International journal of molecular sciences · 2022Review
- Artificial Intelligence in Medical Imaging and its Impact on the Rare Disease Community: Threats, Challenges and Opportunities.PET clinics · 2022Review
- The application of artificial intelligence in lung cancer: a narrative review.Translational cancer research · 2021Review
- Mechanism ofFrontiers in nutrition · 2021Article
- Therapeutic role of corticosteroids in COVID-19: a systematic review of registered clinical trials.Future journal of pharmaceutical sciences · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Different kinds of biological databases publicly available nowadays provide us a goldmine of multidiscipline big data. The Cancer Genome Atlas is a cancer database including detailed information of many patients with cancer. DrugBank is a database including detailed information of approved, investigational and withdrawn drugs, as well as other nutraceutical and metabolite structures. PubChem is a chemical compound database including all commercially available compounds as well as other synthesisable compounds. Protein Data Bank is a crystal structure database including X-ray, cryo-EM and nuclear magnetic resonance protein three-dimensional structures as well as their ligands. On the other hand, artificial intelligence (AI) is playing an important role in the drug discovery progress. The integration of such big data and AI is making a great difference in the discovery of novel targeted drug. In this review, we focus on the currently available advanced methods for the discovery of highly effective lead compounds with great absorption, distribution, metabolism, excretion and toxicity properties.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.