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Electronic Health Record Based Algorithm to Identify Patients with Autism Spectrum Disorder.
Lingren T, Chen P, Bochenek J, Doshi-Velez F, Manning-Courtney P, Bickel J, Wildenger Welchons L, Reinhold J, Bing N, Ni Y, Barbaresi W, Mentch F, Basford M, Denny J, Vazquez L, Perry C, Namjou B, Qiu H, Connolly J, Abrams D, Holm IA, Cobb BA, Lingren N, Solti I, Hakonarson H, Kohane IS, Harley J, Savova G. Lingren T, et al. PLoS One. 2016 Jul 29;11(7):e0159621. doi: 10.1371/journal.pone.0159621. eCollection 2016. PLoS One. 2016. PMID: 27472449 Free PMC article.
OBJECTIVE: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, e …
OBJECTIVE: Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Cl …
Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016.
Srivastava AK, Wang Y, Huang R, Skinner C, Thompson T, Pollard L, Wood T, Luo F, Stevenson R, Polimanti R, Gelernter J, Lin X, Lim IY, Wu Y, Teh AL, Chen L, Aris IM, Soh SE, Tint MT, MacIsaac JL, Yap F, Kwek K, Saw SM, Kobor MS, Meaney MJ, Godfrey KM, Chong YS, Holbrook JD, Lee YS, Gluckman PD, Karnani N; GUSTO study group; Kapoor A, Lee D, Chakravarti A, Maercker C, Graf F, Boutros M, Stamoulis G, Santoni F, Makrythanasis P, Letourneau A, Guipponi M, Panousis N, Garieri M, Ribaux P, Falconnet E, Borel C, Antonarakis SE, Kumar S, Curran J, Blangero J, Chatterjee S, Kapoor A, Akiyama J, Auer D, Berrios C, Pennacchio L, Chakravarti A, Donti TR, Cappuccio G, Miller M, Atwal P, Kennedy A, Cardon A, Bacino C, Emrick L, Hertecant J, Baumer F, Porter B, Bainbridge M, Bonnen P, Graham B, Sutton R, Sun Q, Elsea S, Hu Z, Wang P, Zhu Y, Zhao J, Xiong M, Bennett DA, Hidalgo-Miranda A, Romero-Cordoba S, Rodriguez-Cuevas S, Rebollar-Vega R, Tagliabue E, Iorio M, D’Ippolito E, Baroni S, Kaczkowski B, Tanaka Y, Kawaji H, Sandelin A, Andersson R, Itoh M, Lassmann T; The FANTOM5 Consortium; Hayashizaki Y, Carninci P, Forrest ARR, Semple CA, Rosenthal EA, Shirts B, Amendola L, Gallego C, Horike-Pyne… See abstract for full author list ➔ Srivastava AK, et al. Hum Genomics. 2016 May 26;10 Suppl 1(Suppl 1):12. doi: 10.1186/s40246-016-0063-5. Hum Genomics. 2016. PMID: 27294413 Free PMC article.
O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. ...Ghosh, S. Plon O37 Identification and electronic health record incorporation of clinically actionable pharma …
O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder
Identifying Children and Youth With Autism Spectrum Disorder in Electronic Medical Records: Examining Health System Utilization and Comorbidities.
Brooks JD, Bronskill SE, Fu L, Saxena FE, Arneja J, Pinzaru VB, Anagnostou E, Nylen K, McLaughlin J, Tu K. Brooks JD, et al. Autism Res. 2021 Feb;14(2):400-410. doi: 10.1002/aur.2419. Epub 2020 Oct 24. Autism Res. 2021. PMID: 33098262 Free PMC article.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder requiring significant health and educational resources for affected individuals. ...We developed and validated an algorithm to identify children and youth with ASD wit
Autism spectrum disorder (ASD) is a neurodevelopmental disorder requiring significant health and educatio
A practical approach to identifying autistic adults within the electronic health record.
Malow BA, Veatch OJ, Niu X, Fitzpatrick KA, Hucks D, Maxwell-Horn A, Davis LK. Malow BA, et al. Autism Res. 2023 Jan;16(1):52-65. doi: 10.1002/aur.2849. Epub 2022 Nov 15. Autism Res. 2023. PMID: 36377765 Free PMC article.
The electronic health record (EHR) provides valuable data for understanding physical and mental health conditions in autism. ...Average scores were calculated for each set of charts based on captured CUIs. Chart review determined whether …
The electronic health record (EHR) provides valuable data for understanding physical and mental health condition …
Gut microbiota functional profiling in autism spectrum disorders: bacterial VOCs and related metabolic pathways acting as disease biomarkers and predictors.
Vernocchi P, Marangelo C, Guerrera S, Del Chierico F, Guarrasi V, Gardini S, Conte F, Paci P, Ianiro G, Gasbarrini A, Vicari S, Putignani L. Vernocchi P, et al. Front Microbiol. 2023 Dec 18;14:1287350. doi: 10.3389/fmicb.2023.1287350. eCollection 2023. Front Microbiol. 2023. PMID: 38192296 Free PMC article.
BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays between the gastrointestinal (GI) tract and the central nervous system (CNS) seem to be driven by gut microbiota (GM). ...CONCLUSION: Our resul …
BACKGROUND: Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder. Major interplays bet …
Advancing artificial intelligence-assisted pre-screening for fragile X syndrome.
Movaghar A, Page D, Brilliant M, Mailick M. Movaghar A, et al. BMC Med Inform Decis Mak. 2022 Jun 10;22(1):152. doi: 10.1186/s12911-022-01896-5. BMC Med Inform Decis Mak. 2022. PMID: 35689224 Free PMC article.
The medical complexity of FXS underscores an urgent need to develop more efficient and effective screening methods to identify individuals with FXS. In this study, we evaluate the effectiveness of using artificial intelligence (AI) and electronic health re
The medical complexity of FXS underscores an urgent need to develop more efficient and effective screening methods to identify indivi …
Predicting neurodevelopmental disorders using machine learning models and electronic health records - status of the field.
Rajagopalan SS, Tammimies K. Rajagopalan SS, et al. J Neurodev Disord. 2024 Nov 15;16(1):63. doi: 10.1186/s11689-024-09579-0. J Neurodev Disord. 2024. PMID: 39548397 Free PMC article. Review.
Machine learning (ML) is increasingly used to identify patterns that could predict neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). ...This review summarizes studies …
Machine learning (ML) is increasingly used to identify patterns that could predict neurodevelopmental disorders (NDDs), such as au