首页|University Putra Malaysia Reports Findings in Artificial Intelligence (Review of MR spectroscopy analysis and artificial intelligence applications for the detection of cerebral inflammation and neurotoxicity in Alzheimer's disease)
University Putra Malaysia Reports Findings in Artificial Intelligence (Review of MR spectroscopy analysis and artificial intelligence applications for the detection of cerebral inflammation and neurotoxicity in Alzheimer's disease)
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New research on Artificial Intelligence is the subject of a report. According to news reporting originating in Selangor, Malaysia, by NewsRx journalists, research stated, “Magnetic resonance spectroscopy (MRS) has an emerging role as a neuroimaging tool for the detection of biomarkers of Alzheimer’s disease (AD). To date, MRS has been established as one of the diagnostic tools for various diseases such as breast cancer and fatty liver, as well as brain tumours.” The news reporters obtained a quote from the research from University Putra Malaysia, “However, its utility in neurodegenerative diseases is still in the experimental stages. The potential role of the modality has not been fully explored, as there is diverse information regarding the aberrations in the brain metabolites caused by normal ageing versus neurodegenerative disorders. A literature search was carried out to gather eligible studies from the following widely sourced electronic databases such as Scopus, PubMed and Google Scholar using the combination of the following keywords: AD, MRS, brain metabolites, deep learning (DL), machine learning (ML) and artificial intelligence (AI); having the aim of taking the readers through the advancements in the usage of MRS analysis and related AI applications for the detection of AD. We elaborate on the MRS data acquisition, processing, analysis, and interpretation techniques. Recommendation is made for MRS parameters that can obtain the best quality spectrum for fingerprinting the brain metabolomics composition in AD. Furthermore, we summarise ML and DL techniques that have been utilised to estimate the uncertainty in the machine-predicted metabolite content, as well as streamline the process of displaying results of metabolites derangement that occurs as part of ageing.”
SelangorMalaysiaAsiaAlzheimer DiseaseArtificial IntelligenceBiomarkersBrain Diseases and ConditionsCentral Nervous System Diseases and ConditionsDementiaDiagnostics and ScreeningEmerging TechnologiesHealth and MedicineInflammationMachine LearningNeurodegenerative Diseases and ConditionsTauopathies
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