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Cited by 48Artificial Intelligence in Healthcare and EducationArtificial Intelligence in HealthcareArtificial Intelligence Applications

Revolutionizing Neurology: The Role of Artificial Intelligence in Advancing Diagnosis and Treatment

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Kalani, Meetali, Anjankar, Ashish·2024·Cureus
DOI 10.7759/cureus.61706PMC PMC11224934
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Abstract

Artificial intelligence (AI) has emerged as a powerful tool in the field of neurology, significantly impacting the diagnosis and treatment of neurological disorders. Recent technological breakthroughs have given us access to a plethora of information relevant to many aspects of neurology. Neuroscience and AI share a long history of collaboration. Along with great potential, we encounter obstacles relating to data quality, ethics, and inherent difficulty in applying data science in healthcare. Neurological disorders pose intricate challenges due to their complex manifestations and variability. Automating image interpretation tasks, AI algorithms accurately identify brain structures and detect abnormalities. This accelerates diagnosis and reduces the workload on medical professionals. Treatment optimization benefits from AI simulations that model different scenarios and predict outcomes. These AI systems can currently perform many of the sophisticated perceptual and cognitive capacities of biological systems, such as object identification and decision making. Furthermore, AI is rapidly being used as a tool in neuroscience research, altering our understanding of brain functioning. It has the ability to revolutionize healthcare as we know it into a system in which humans and robots collaborate to deliver better care for our patients. Image analysis activities such as recognizing particular brain regions, calculating changes in brain volume over time, and detecting abnormalities in brain scans can be automated by AI systems. This lessens the strain on radiologists and neurologists while improving diagnostic accuracy and efficiency. It is now obvious that cutting-edge artificial intelligence models combined with high-quality clinical data will lead to enhanced prognostic and diagnostic models in neurological illness, permitting expert-level clinical decision aids across healthcare settings. In conclusion, AI's integration into neurology has revolutionized diagnosis, treatment, and research. As AI technologies advance, they promise to unravel the complexities of neurological disorders further, leading to improved patient care and quality of life. The symbiosis of AI and neurology offers a glimpse into a future where innovation and compassion converge to reshape neurological healthcare. This abstract provides a concise overview of the role of AI in neurology and its transformative potential.

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  • The framework's modular and adaptable design supports broad generalizability across diverse clinical domains beyond cardiovascular diagnoses, such as oncology, neurology, and infectious diseases.

    “Its modular and adaptable design supports broad generalizability across diverse clinical domains beyond cardiovascular diagnoses, such as oncology, neurology, and infectious diseases [37,38,39].”

    From Enhancing Clinician Trust in AI Diagnostics: A Dynamic Framework for Confidence Calibration and Transparency (2025) · cites this paper as [37]

    The Introduction and Review discuss AI applications in neurology and the importance of models generalizing to diverse populations. Neither those passages nor searches for a modular framework and cross-domain use address whether the citing paper’s framework can generalize beyond cardiovascular diagnosis to oncology, neurology, and infectious diseases. (LLM, conf=0.75)

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Cited by

Sorted by citations

Authors
Kalani, M., & Anjankar, A.
Affiliations
Datta Meghe Institute of Higher Education and Research (IN)
Corresponding author
Kalani, Meetali
ORCID
Anjankar, Ashish
Venue
Cureus
Publisher
Springer Science and Business Media LLC
Published
2024-06-05
Volume
16
Issue
6
Pages
e61706-e61706
ISSN
2168-8184 (ISSN-L)
DOI
10.7759/cureus.61706
PMC
PMC11224934
OpenAlex
W4399359461
Cited by
48
References
5
Citations by year
2026: 16 · 2025: 29 · 2024: 3
FWCI
1.09
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Cureus (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
artificial intelligence in neurology, neurological disorders, brain structure segmentation, clinical decision support, treatment optimization, diagnostic accuracy

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