Correction: Dynamic magnetic characterization and magnetic particle imaging enhancement of magnetic-gold core–shell nanoparticles

Tomitaka, Asahi; Ota, Satoshi; Nishimoto, Kizuku; Arami, Hamed; Takemura, Yasushi; Nair, M. G.

doi:10.1039/d0nr90220a

Cited by 2 publications

(1 citation statement)

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“…One of the primary applications of AI in diagnosing neurological illnesses is the interpretation of medical imaging data. By identifying patterns and features in imaging data, AI systems can detect abnormalities connected to specific neurological conditions, such as stroke, brain tumours, multiple sclerosis, and Alzheimer's disease [16]. These techniques can aid radiologists in locating lesions, enhancing diagnostic accuracy, and reducing interpretation variability.…”

Section: Diagnosis Of Neurological Diseasesmentioning

confidence: 99%

Operating Artificial Intelligence to Assist Physicians Diagnose Medical Images: A Narrative Review

Adelaja,

Alkattan

2023

MJAIH

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Medical image diagnostics is crucial to healthcare since it aids in the diagnosis and treatment of a variety of diseases and conditions. However, the process is time-consuming and prone to human error. In recent years, artificial intelligence has been a powerful tool for enhancing medical imaging diagnosis. Using AI algorithms for medical picture interpretation has the potential to revolutionise the field by improving accuracy, efficacy, and standardization. These algorithms can quickly sift through enormous amounts of medical imaging, finding anomalies, quantifying features, and providing useful information to help medical professionals make judgments. AI-based systems can be used to track the evolution of diseases, plan treatments, and highlight particular areas of interest in medical pictures. Additionally, AI systems can aid in case triage by classifying cases according to urgency, enabling quick response to life-or-death situations. Healthcare practitioners can gain from increased diagnostic accuracy and efficiency, improved workflow management, and standardized interpretations by utilizing AI in medical imaging diagnostics. However, it's crucial to understand that AI complements human expertise rather than replacing it. To ensure a safe and efficient application in clinical settings as AI technologies continue to evolve and advance, continuing research and collaboration between AI developers and healthcare practitioners is essential. Medical image diagnosis is poised to advance significantly with continued AI integration, ultimately improving patient outcomes and healthcare delivery.

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Section: Diagnosis Of Neurological Diseasesmentioning

confidence: 99%