The evolution of Big Data in neuroscience and neurology

Dipietro, Laura; Gonzalez-Mego, Paola; Ramos-Estebanez, Ciro; Zukowski, Lauren Hana; Mikkilineni, Rahul; Rushmore, Richard Jarrett; Wagner, Timothy

doi:10.1186/s40537-023-00751-2

Journal of Big Data

Table 5 Sample of SUD and OUD “Big Data” Studies

From: The evolution of Big Data in neuroscience and neurology

Refs	Year	Author	Vol	Var	Vel	Ver	Val
[280]	2016	Kohno	39 methamphetamine (MA)-dependent subjects and 44 HC	Clinical, Imaging (e.g., rs-fMRI, PET)	F	A	C
[203]	2016	Mackey	> 10,000 subjects (review)	Imaging (e.g., MRI), genetic	O	A	C
[16]	2017	Kim	NA	Social media-based metrics (e.g., number of likes on Facebook groups)	NA	NA	C
[160]	2017	Sanchez-Roige	> 120,000 patients	Alcohol Use Disorders Identification Test (AUDIT), genetics	F	A	C
[281]	2018	Ipser	46 MA-dependent subjects and 26 HC	Clinical, Imaging (e.g., rs-fMRI)	F	A	C
[282]	2018	Lisdahl	12,000 youth (21 US sites) [283]	Cognitive, clinical (SUD focus), culture & environment, imaging (e.g., MRI), and bioassays	O	A	C
[284]	2018	Sun	78 heroin abusers and 79 HC	Imaging (e.g., DTI), clinical, and genetic	F	A	C
[159]	2019	Mackey	23 labs, 2,140 SUD, 1100 HC	Imaging (e.g., MRI), clinical for alcohol, nicotine, cocaine, methamphetamine, or cannabis dependent patients	O	A	C
[285]	2019	Yip	74 methadone-maintained, cocaine-dependent subjects	Imaging (e.g., fMRI), data from Monetary Incentive Delay task, clinical	F	A	C
[286]	2019	Young	NA-This is a viewpoint paper	Social media posts, location, cannabis outcomes	NA	NA	C
[161]	2020	Cuomo	10 M tweets- > 257 tweets about opioids, IV Drug Use or HIV hospitalizations and HIV cases	Twitter data, hospitalizations, and new HIV cases	F(SM)	Mix	C
[287]	2020	Segal	“10 M medical insurance claims” “from 550,000 patient records”	Diagnosis & procedures, medications, episode counts	O	A	C
[122]	2020	Slade	11,778,912 records, 118,063 with adolescent ADHD medication	Longitudinal clinical and medication hx, demographics	F	A	PC
[288]	2020	Zhou	> 10,000 European ancestry OUD; > 70,000 opioid-exposed control > 5000 African ancestry OUD; > 25,000 opioid-exposed control	Genetic, clinical	O	A
[37]	2020	Thompson	33 sites, 12,347 individuals (including 2277 adults with SUD (alcohol, nicotine, cocaine, MA, or cannabis)	Imaging (e.g., MRI), clinical, genetic, and epigenetic	O	A	C
[289]	2021	Flores	19,721 tweets identified with opioid keywords across 7 US cities	Tweets, geolocation	O(SM)	Mix	C
[290]	2021	Gelernter	NA	Clinical, genetics	NA	NA	C
[291]	2021	Liu	31 heroin users	Clinical, imaging (e.g., fMRI during visual cues)	F	A	C
[292]	2021	Purushothaman	“56,464 Instagram posts and comments”, including 719 posts containing “suicide, substance use and/or mental health”	Instagram posts	O(SM)*	Mix	C
[293]	2021	Rosetti	660 Alcohol Dependence, 326 controls	Imaging (e.g., DTI, MRI), clinical (e.g., drug use)	O	A	C
[294]	2021	Tretter	NA	NA	NA	NA	C
[158]	2022	Hayes	> 9 M veterans	Clinical, insurance claims, imaging (e.g., fMRI), genetics	O	A	C
[295]	2022	Li	46 MA-dependent subjects and 40 HC	Clinical, imaging (e.g., rs-fMRI)	F	A	C
[296]	2022	Ottino-Gonzalez	> 700 subjects (cocaine (n = 147), MA (n = 132) nicotine (n = 189), and HC = 333)	Imaging (DTI, MRI), clinical (e.g., drug use)	O	A	C

We have classified the example citations [16, 122, 159,160,161, 203, 280,281,282, 284,285,286,287,288,289,290,291,292,293,294,295,296,297] with the classic 5 V’s definition. However, these are not always clearly defined in the prospective studies, retrospective studies, or review articles. For Volume (Vol): We focused on the size of patient cohorts. For Variety: We indicate the different data and specimen types derived from the cohorts (note, Variety can also be seen in patient type, tabulated in Volume; and vice versa the data type is indicative of volume indicated in Variety). For Velocity (Vol): We reported the data Velocity as either ‘F’ for Fixed studies (analyzing data from databases or studies which are no longer acquiring data) or ‘O’ for Ongoing studies (analyzing data from databases or clinical studies that are still acquiring data, although it should be noted that the reported results of the studies are based on analysis of a fixed data set with the noted volume at the time of the publication). We also indicate if any “real-time” data was or will be gathered as part of the study (SM Social Media Dependent). Where any type of velocity information is given, and a velocity calculation can be made, it is provided in the Additional file 1: Table S5 (and noted herein with a *). For Veracity (Vol): M Manual verification, A Data verified through automated analytical process (AI, statistical methods), and Mix Automated Analytical and Manual (or semi-automated). However, all experimental data veracity is dependent on the methodological limitations of the core studies; thus, we also provide examples of variability or error in the Additional file 1: Table S5. For Value (Vol): As neither study costs are disclosed, health economics assessments completed, nor a monetary cost assigned in the sale or purchase of any of the above data sets, we report “P” for Preclinical, “C” for Clinical value or “PC” for Preclinical and Clinical, dependent on the study species and data use. The limitations to these definitions and study information availability are described in the text (e.g., see “Proposed Solutions”). In the Additional file 1, Additional file 1: Table S5, we also include information on the tools used, database source(s), and methodological limitations. For Year we indicate the year of the earliest publication. hx history

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