FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3134680770> ?p ?o ?g. }

• W3134680770 endingPage "2761" @default.
• W3134680770 startingPage "2761" @default.
• W3134680770 abstract "Background: Alzheimer’s disease (AD) is a complex and severe neurodegenerative disease that still lacks effective methods of diagnosis. The current diagnostic methods of AD rely on cognitive tests, imaging techniques and cerebrospinal fluid (CSF) levels of amyloid-β1-42 (Aβ42), total tau protein and hyperphosphorylated tau (p-tau). However, the available methods are expensive and relatively invasive. Artificial intelligence techniques like machine learning tools have being increasingly used in precision diagnosis. Methods: We conducted a meta-analysis to investigate the machine learning and novel biomarkers for the diagnosis of AD. Methods: We searched PubMed, the Cochrane Central Register of Controlled Trials, and the Cochrane Database of Systematic Reviews for reviews and trials that investigated the machine learning and novel biomarkers in diagnosis of AD. Results: In additional to Aβ and tau-related biomarkers, biomarkers according to other mechanisms of AD pathology have been investigated. Neuronal injury biomarker includes neurofiliament light (NFL). Biomarkers about synaptic dysfunction and/or loss includes neurogranin, BACE1, synaptotagmin, SNAP-25, GAP-43, synaptophysin. Biomarkers about neuroinflammation includes sTREM2, and YKL-40. Besides, d-glutamate is one of coagonists at the NMDARs. Several machine learning algorithms including support vector machine, logistic regression, random forest, and naïve Bayes) to build an optimal predictive model to distinguish patients with AD from healthy controls. Conclusions: Our results revealed machine learning with novel biomarkers and multiple variables may increase the sensitivity and specificity in diagnosis of AD. Rapid and cost-effective HPLC for biomarkers and machine learning algorithms may assist physicians in diagnosing AD in outpatient clinics." @default.
• W3134680770 created "2021-03-15" @default.
• W3134680770 creator A5000923658 @default.
• W3134680770 creator A5037096530 @default.
• W3134680770 creator A5058055584 @default.
• W3134680770 date "2021-03-09" @default.
• W3134680770 modified "2023-10-17" @default.
• W3134680770 title "Machine Learning and Novel Biomarkers for the Diagnosis of Alzheimer’s Disease" @default.
• W3134680770 cites W1529527003 @default.
• W3134680770 cites W1570236416 @default.
• W3134680770 cites W1936322111 @default.
• W3134680770 cites W1972025839 @default.
• W3134680770 cites W1974300727 @default.
• W3134680770 cites W1984924722 @default.
• W3134680770 cites W1997306216 @default.
• W3134680770 cites W2003432290 @default.
• W3134680770 cites W2013391120 @default.
• W3134680770 cites W2017273813 @default.
• W3134680770 cites W2027908253 @default.
• W3134680770 cites W2028174194 @default.
• W3134680770 cites W2030950431 @default.
• W3134680770 cites W2038003677 @default.
• W3134680770 cites W2055285182 @default.
• W3134680770 cites W2061600370 @default.
• W3134680770 cites W2065338300 @default.
• W3134680770 cites W2080274663 @default.
• W3134680770 cites W2082151254 @default.
• W3134680770 cites W2092946080 @default.
• W3134680770 cites W2093650784 @default.
• W3134680770 cites W2114222094 @default.
• W3134680770 cites W2115017507 @default.
• W3134680770 cites W2125269329 @default.
• W3134680770 cites W2171032841 @default.
• W3134680770 cites W2288973352 @default.
• W3134680770 cites W2328133047 @default.
• W3134680770 cites W2473213421 @default.
• W3134680770 cites W2521991649 @default.
• W3134680770 cites W2560512986 @default.
• W3134680770 cites W2601368841 @default.
• W3134680770 cites W2733247491 @default.
• W3134680770 cites W2765374660 @default.
• W3134680770 cites W2766125374 @default.
• W3134680770 cites W2784429314 @default.
• W3134680770 cites W2787427645 @default.
• W3134680770 cites W2792251793 @default.
• W3134680770 cites W2896396037 @default.
• W3134680770 cites W2900116592 @default.
• W3134680770 cites W2912108320 @default.
• W3134680770 cites W2912556930 @default.
• W3134680770 cites W2943103900 @default.
• W3134680770 cites W2943938689 @default.
• W3134680770 cites W2945705997 @default.
• W3134680770 cites W2963423764 @default.
• W3134680770 cites W2964171289 @default.
• W3134680770 cites W2964629181 @default.
• W3134680770 cites W2967294656 @default.
• W3134680770 cites W2969226503 @default.
• W3134680770 cites W2996431818 @default.
• W3134680770 cites W3000240575 @default.
• W3134680770 cites W3004379845 @default.
• W3134680770 cites W3023079706 @default.
• W3134680770 cites W3033758968 @default.
• W3134680770 cites W3040008283 @default.
• W3134680770 cites W3040413343 @default.
• W3134680770 cites W3048501039 @default.
• W3134680770 cites W3083002817 @default.
• W3134680770 cites W3084423159 @default.
• W3134680770 cites W3093401392 @default.
• W3134680770 cites W3112682090 @default.
• W3134680770 cites W3113755162 @default.
• W3134680770 cites W3116132399 @default.
• W3134680770 cites W3129233394 @default.
• W3134680770 doi "https://doi.org/10.3390/ijms22052761" @default.
• W3134680770 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7963160" @default.
• W3134680770 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33803217" @default.
• W3134680770 hasPublicationYear "2021" @default.
• W3134680770 type Work @default.
• W3134680770 sameAs 3134680770 @default.
• W3134680770 citedByCount "60" @default.
• W3134680770 countsByYear W31346807702021 @default.
• W3134680770 countsByYear W31346807702022 @default.
• W3134680770 countsByYear W31346807702023 @default.
• W3134680770 crossrefType "journal-article" @default.
• W3134680770 hasAuthorship W3134680770A5000923658 @default.
• W3134680770 hasAuthorship W3134680770A5037096530 @default.
• W3134680770 hasAuthorship W3134680770A5058055584 @default.
• W3134680770 hasBestOaLocation W31346807701 @default.
• W3134680770 hasConcept C119857082 @default.
• W3134680770 hasConcept C12267149 @default.
• W3134680770 hasConcept C142724271 @default.
• W3134680770 hasConcept C154945302 @default.
• W3134680770 hasConcept C169258074 @default.
• W3134680770 hasConcept C181199279 @default.
• W3134680770 hasConcept C195794163 @default.
• W3134680770 hasConcept C2776478404 @default.
• W3134680770 hasConcept C2779134260 @default.
• W3134680770 hasConcept C2779483572 @default.
• W3134680770 hasConcept C2780748493 @default.

• next