Early detection of neurological diseases using machine learning and deep learning techniques: A review

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

“…One of the most critical aspects of treating neurological disorders is early diagnosis, which often remains challenging due to neurological symptoms' complex and subtle nature. AI algorithms can process extensive patient data, including medical histories, imaging results, and genetic information, to identify fine markers that human experts might overlook [7]. Transcranial Doppler (TCD) ultrasonography is a non-invasive approach for diagnosing cerebrovascular illness that employs the Doppler effect to identify the hemodynamic and physiological characteristics of the primary intracranial basilar arteries.…”

“…AI has proven to be a game changer, with its ability to extract insights from different datasets such as medical scans, genetic profiles, and patient histories [6]. The benefits of AI in neurology are far-reaching and multifaceted, extending across early diagnosis, personalized treatment, BCIs, neuroimaging analysis, treatment optimization, and even drug development [7]. As AI evolves and matures, its potential to revolutionize neurological healthcare becomes increasingly evident [8].…”

Automated Detection of Plant Leaf Diseases using Image Processing Techniques

“…Some of the most common plant leaf diseases include powdery mildew, rust, and bacterial blight. Each of these diseases has distinct visual symptoms, making it possible to diagnose them based on their appearance [14].…”