AIMC Topic: Brain Diseases

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Blurring the boundaries between frame-based and frameless stereotaxy: feasibility study for brain biopsies performed with the use of a head-mounted robot.

Journal of neurosurgery
OBJECT: Frame-based stereotactic interventions are considered the gold standard for brain biopsies, but they have limitations with regard to flexibility and patient comfort because of the bulky head ring attached to the patient. Frameless image guida...

A review of artificial intelligence-based brain age estimation and its applications for related diseases.

Briefings in functional genomics
The study of brain age has emerged over the past decade, aiming to estimate a person's age based on brain imaging scans. Ideally, predicted brain age should match chronological age in healthy individuals. However, brain structure and function change ...

A Cross-Feature Mutual Learning Framework to Integrate Functional Connectivity and Activity for Brain Disorder Classification.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Time courses (TC) and functional network connectivity (FNC) features, derived from functional magnetic resonance imaging, show considerable potential in the study of brain disorders. Despite significant advancements, most deep learning approaches ten...

Brain Disorder Detection and Diagnosis using Machine Learning and Deep Learning - A Bibliometric Analysis.

Current neuropharmacology
BACKGROUND AND OBJECTIVE: Brain disorders are one of the major global mortality issues, and their early detection is crucial for healing. Machine learning, specifically deep learning, is a technology that is increasingly being used to detect and diag...

Cryptic mutations of PLC family members in brain disorders: recent discoveries and a deep-learning-based approach.

Brain : a journal of neurology
Phospholipase C (PLC) is an essential isozyme involved in the phosphoinositide signalling pathway, which maintains cellular homeostasis. Gain- and loss-of-function mutations in PLC affect enzymatic activity and are therefore associated with several d...

Clinical Artificial Intelligence Applications in Radiology: Neuro.

Radiologic clinics of North America
Radiologists have been at the forefront of the digitization process in medicine. Artificial intelligence (AI) is a promising area of innovation, particularly in medical imaging. The number of applications of AI in neuroradiology has also grown. This ...

Deep learning for brain disorders: from data processing to disease treatment.

Briefings in bioinformatics
In order to reach precision medicine and improve patients' quality of life, machine learning is increasingly used in medicine. Brain disorders are often complex and heterogeneous, and several modalities such as demographic, clinical, imaging, genetic...

Machine learning for classification and prediction of brain diseases: recent advances and upcoming challenges.

Current opinion in neurology
PURPOSE OF REVIEW: Machine learning is an artificial intelligence technique that allows computers to perform a task without being explicitly programmed. Machine learning can be used to assist diagnosis and prognosis of brain disorders. Although the e...

MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide.

Brain : a journal of neurology
Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In particular, MRI-derived brain age has been used as a compr...

A natural evolution optimization based deep learning algorithm for neurological disorder classification.

Bio-medical materials and engineering
BACKGROUND: A neurological disorder is one of the significant problems of the nervous system that affects the essential functions of the human brain and spinal cord. Monitoring brain activity through electroencephalography (EEG) has become an importa...