ReviewAnnals of translational medicine2020
The combination of brain-computer interfaces and artificial intelligence: applications and challenges.
Review in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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
39 citing papers in PubMed, 113 citations in OpenAlex.
- Towards neuromorphic neurotechnologies: integrating brain-inspired computing with brain-computer interfaces.npj biomedical innovations · 2026Review
- Neural Vision Restoration in Ophthalmology.Annals of biomedical engineering · 2026Review
- Redefining Stroke Care with Artificial Intelligence: Recent Advances.Current neurology and neuroscience reports · 2026Review
- Bridging cognition and control through passive eye movement integration in motor imagery brain-computer interfaces.Frontiers in human neuroscience · 2026Review
- [Ethical considerations for artificial intelligence-enhanced brain-computer interface].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Article
- Does brain-computer interface-based mind reading threaten mental privacy? ethical reflections from interviews with Chinese experts.BMC medical ethics · 2025Article
- Directional hand movement can be classified from insular cortex SEEG signals using recurrent neural networks and high-gamma band features.Scientific reports · 2025Article
- Evolutionary Trajectories of Consciousness: From Biological Foundations to Technological Horizons.Brain sciences · 2025Review
- Improving EEG based brain computer interface emotion detection with EKO ALSTM model.Scientific reports · 2025Article
- Exploring the intersection of brain-computer interfaces and traditional, complementary, and integrative medicine.Integrative medicine research · 2025Article
- Neurophysiological Approaches to Lie Detection: A Systematic Review.Brain sciences · 2025Review
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Artificial Intelligence for Patient Safety and Surgical Education in Neurosurgery.JMA journal · 2025Review
- Advancements in the application of brain-computer interfaces based on different paradigms in amyotrophic lateral sclerosis.Frontiers in neuroscience · 2025Review
- Signal acquisition of brain-computer interfaces: A medical-engineering crossover perspective review.Fundamental research · 2025Review
- Exploring the Impact of Brain-Computer Interfaces on Health Care: Innovations, Challenges, and Future Prospects: A Review Article.Journal of pharmacy & bioallied sciences · 2024Review
- Electroencephalography-Based Brain-Computer Interfaces in Rehabilitation: A Bibliometric Analysis (2013-2023).Sensors (Basel, Switzerland) · 2024Review
- Neural interfaces: Bridging the brain to the world beyond healthcare.Exploration (Beijing, China) · 2024Article
- Artificial Intelligence and Deep Learning in Revolutionizing Brain Tumor Diagnosis and Treatment: A Narrative Review.Cureus · 2024Review
- Decentralising the Self - Ethical Considerations in Utilizing Decentralised Web Technology for Direct Brain Interfaces.Science and engineering ethics · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain-computer interfaces (BCIs) have shown great prospects as real-time bidirectional links between living brains and actuators. Artificial intelligence (AI), which can advance the analysis and decoding of neural activity, has turbocharged the field of BCIs. Over the past decade, a wide range of BCI applications with AI assistance have emerged. These "smart" BCIs including motor and sensory BCIs have shown notable clinical success, improved the quality of paralyzed patients' lives, expanded the athletic ability of common people and accelerated the evolution of robots and neurophysiological discoveries. However, despite technological improvements, challenges remain with regard to the long training periods, real-time feedback, and monitoring of BCIs. In this article, the authors review the current state of AI as applied to BCIs and describe advances in BCI applications, their challenges and where they could be headed in the future.
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.