Matches in SemOpenAlex for { <https://semopenalex.org/work/W4319335144> ?p ?o ?g. }
- W4319335144 abstract "Abstract Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classification of clinical disorders due to the lack of robust and objective biomarkers. This review provides an overview of research on psychiatric diseases by using fNIRS and ML. Article search was carried out and 45 studies were evaluated by considering their sample sizes, used features, ML methodology, and reported accuracy. To our best knowledge, this is the first review that reports diagnostic ML applications using fNIRS. We found that there has been an increasing trend to perform ML applications on fNIRS-based biomarker research since 2010. The most studied populations are schizophrenia (n=12), attention deficit and hyperactivity disorder (n=7), and autism spectrum disorder (n=6) are the most studied populations. There is a significant negative correlation between sample size (>20) and accuracy values. Support vector machine (SVM) and deep learning (DL) approaches were the most popular classifier approaches (SVM = 20) (DL = 10). Eight of these studies recruited a number of participants more than 100 for classification. Change in oxy-hemoglobin (ΔHbO) based features were used more than change in deoxy-hemoglobin-based ones and the most popular ΔHbO-based features were mean ΔHbO (n=11) and ΔHbO-based functional connections (n=11). Using ML on fNIRS data might be a promising approach to reveal specific biomarkers for diagnostic classification." @default.
- W4319335144 created "2023-02-08" @default.
- W4319335144 creator A5000102473 @default.
- W4319335144 creator A5021123752 @default.
- W4319335144 creator A5059662515 @default.
- W4319335144 date "2023-02-07" @default.
- W4319335144 modified "2023-10-17" @default.
- W4319335144 title "Diagnostic Machine Learning Approaches on Clinical Populations and Clinical Conditions using Functional Near Infrared Spectroscopy : A Review" @default.
- W4319335144 cites W1906317191 @default.
- W4319335144 cites W1989181595 @default.
- W4319335144 cites W1999340799 @default.
- W4319335144 cites W2000415220 @default.
- W4319335144 cites W2018358125 @default.
- W4319335144 cites W2019489038 @default.
- W4319335144 cites W2035904604 @default.
- W4319335144 cites W2037722933 @default.
- W4319335144 cites W2039101156 @default.
- W4319335144 cites W2045561515 @default.
- W4319335144 cites W2049812766 @default.
- W4319335144 cites W2058069901 @default.
- W4319335144 cites W2060477798 @default.
- W4319335144 cites W2066845773 @default.
- W4319335144 cites W2078524519 @default.
- W4319335144 cites W2081349230 @default.
- W4319335144 cites W2082504982 @default.
- W4319335144 cites W2084187427 @default.
- W4319335144 cites W2092890379 @default.
- W4319335144 cites W2098521030 @default.
- W4319335144 cites W2103904600 @default.
- W4319335144 cites W2110006603 @default.
- W4319335144 cites W2114925382 @default.
- W4319335144 cites W2115223657 @default.
- W4319335144 cites W2121265355 @default.
- W4319335144 cites W2143937412 @default.
- W4319335144 cites W2145680887 @default.
- W4319335144 cites W2158485497 @default.
- W4319335144 cites W2162381600 @default.
- W4319335144 cites W2163271186 @default.
- W4319335144 cites W2169264770 @default.
- W4319335144 cites W2197869044 @default.
- W4319335144 cites W2310177520 @default.
- W4319335144 cites W2322983841 @default.
- W4319335144 cites W2480195998 @default.
- W4319335144 cites W2512068169 @default.
- W4319335144 cites W2528820625 @default.
- W4319335144 cites W2606546398 @default.
- W4319335144 cites W2763594885 @default.
- W4319335144 cites W2770084542 @default.
- W4319335144 cites W2773133415 @default.
- W4319335144 cites W2776637757 @default.
- W4319335144 cites W2782501049 @default.
- W4319335144 cites W2790871287 @default.
- W4319335144 cites W2796292575 @default.
- W4319335144 cites W2800350051 @default.
- W4319335144 cites W2800854546 @default.
- W4319335144 cites W2803754280 @default.
- W4319335144 cites W2805234167 @default.
- W4319335144 cites W2806883049 @default.
- W4319335144 cites W2810339787 @default.
- W4319335144 cites W2909619163 @default.
- W4319335144 cites W2912720239 @default.
- W4319335144 cites W2915893085 @default.
- W4319335144 cites W2917368873 @default.
- W4319335144 cites W2951373364 @default.
- W4319335144 cites W2955286582 @default.
- W4319335144 cites W2963389298 @default.
- W4319335144 cites W2969226503 @default.
- W4319335144 cites W2969915343 @default.
- W4319335144 cites W2980628457 @default.
- W4319335144 cites W2981605752 @default.
- W4319335144 cites W2981679558 @default.
- W4319335144 cites W2988143880 @default.
- W4319335144 cites W2991344754 @default.
- W4319335144 cites W2999524883 @default.
- W4319335144 cites W3004127313 @default.
- W4319335144 cites W3005328682 @default.
- W4319335144 cites W3016342624 @default.
- W4319335144 cites W3016716658 @default.
- W4319335144 cites W3026272888 @default.
- W4319335144 cites W3027309739 @default.
- W4319335144 cites W3042526937 @default.
- W4319335144 cites W3045370469 @default.
- W4319335144 cites W3092169073 @default.
- W4319335144 cites W3100120625 @default.
- W4319335144 cites W3102097205 @default.
- W4319335144 cites W3117800408 @default.
- W4319335144 cites W3126226315 @default.
- W4319335144 cites W3126917856 @default.
- W4319335144 cites W3128939245 @default.
- W4319335144 cites W3133302653 @default.
- W4319335144 cites W3150581858 @default.
- W4319335144 cites W3153875331 @default.
- W4319335144 cites W3156637884 @default.
- W4319335144 cites W3159577154 @default.
- W4319335144 cites W3196295132 @default.
- W4319335144 cites W3201174872 @default.
- W4319335144 cites W3205845732 @default.
- W4319335144 cites W4206589170 @default.
- W4319335144 cites W4220862305 @default.
- W4319335144 cites W4223465279 @default.