ArticleAnesthesia and analgesia2020
Machine-Learning Implementation in Clinical Anesthesia: Opportunities and Challenges.
Article in Anesthesia and analgesia, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence and its clinical application in Anesthesiology: a systematic review.Journal of clinical monitoring and computing · 2024Pooled it
- Integrating multidimensional nociceptive-related cortical features for unsupervised assessment of anesthesia states in rats.iScience · 2026Article
- Impact of a tripartite framework on perioperative clinical reasoning in junior anaesthesiology residents in China: a longitudinal quasi-experimental study.BMC medical education · 2026Article
- A Machine Learning-Based Nomogram for Predicting Overall Survival in BCLC Stage 0-B Hepatocellular Carcinoma Patients with Low HALP Score.Journal of inflammation research · 2026Article
- Developing a machine learning-based prediction model for postinduction hypotension.Journal of clinical monitoring and computing · 2025Article
- Artificial Intelligence in Anesthesia: Enhancing Precision, Safety, and Global Access Through Data-Driven Systems.Journal of clinical medicine · 2025Review
- Development and validation of a machine learning model for cardiovascular disease risk prediction in type 2 diabetes patients.Scientific reports · 2025Article
- Application of machine learning models to explore prognosis and cause of death in advanced intrahepatic cholangiocarcinoma patients undergoing chemotherapy.Discover oncology · 2025Article
- Leveraging machine learning in nursing: innovations, challenges, and ethical insights.Frontiers in digital health · 2025Review
- Enhancing Delirium Prediction and Prevention in Elderly Patients Through Machine Learning-Based Analysis.Sultan Qaboos University medical journal · 2025Article
- Optimising artificial intelligence ultrasound tools in anaesthesiology and perioperative medicine: The next frontier for advanced technology application.Indian journal of anaesthesia · 2024Article
- Physician's autonomy in the face of AI support: walking the ethical tightrope.Frontiers in medicine · 2024Article
- SAP BusinessObjects in Medical Informatics.Cureus · 2023Article
- Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions.Medicinal research reviews · 2021Review
- What Makes Artificial Intelligence Exceptional in Health Technology Assessment?Frontiers in artificial intelligence · 2021Review
- Applications of artificial intelligence in anesthesia: A systematic review.Saudi journal of anaesthesiaReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
PubMed holds no abstract for this paper.
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.