Vidul Ayakulangara Panickan

Vidul Ayakulangara Panickan, MS

Research Associate in Biomedical Informatics
Research Scholar, Harvard-MIT Center for Regulatory Science
Cai Lab

Vidul Ayakulangara Panickan obtained his B.Tech in Computer Science and Engineering from Amrita Vishwa Vidyapeetham (Kollam, India) in 2015. Ayakulangara then pursued a Masters in Computer Science with a focus on Machine Learning from the University of Massachusetts Amherst. He joined DBMI as a Research Associate in October 2019. Ayakulangara is focused on leveraging Natural Language Processing in the task of information extraction from Electronic Medical Records and optimizing algorithms for large scale data processing. He is interested in developing intelligent tools for automating data extraction and aggregation with the goal of expediting research in healthcare.

Endovascular Aneurysm Repair Devices as a Use Case for Postmarketing Surveillance of Medical Devices.
Authors: Wang X, Ayakulangara Panickan V, Cai T, Xiong X, Cho K, Cai T, Bourgeois FT.
JAMA Intern Med
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Diversity and Scale: Genetic Architecture of 2,068 Traits in the VA Million Veteran Program.
Authors: Verma A, Huffman JE, Rodriguez A, Conery M, Liu M, Ho YL, Kim Y, Heise DA, Guare L, Panickan VA, Garcon H, Linares F, Costa L, Goethert I, Tipton R, Honerlaw J, Davies L, Whitbourne S, Cohen J, Posner DC, Sangar R, Murray M, Wang X, Dochtermann DR, Devineni P, Shi Y, Nandi TN, Assimes TL, Brunette CA, Carroll RJ, Clifford R, Duvall S, Gelernter J, Hung A, Iyengar SK, Joseph J, Kember R, Kranzler H, Levey D, Luoh SW, Merritt VC, Overstreet C, Deak JD, Grant SFA, Polimanti R, Roussos P, Sun YV, Venkatesh S, Voloudakis G, Justice A, Begoli E, Ramoni R, Tourassi G, Pyarajan S, Tsao PS, O'Donnell CJ, Muralidhar S, Moser J, Casas JP, Bick AG, Zhou W, Cai T, Voight BF, Cho K, Gaziano MJ, Madduri RK, Damrauer SM, Liao KP.
medRxiv
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Generate Analysis-Ready Data for Real-world Evidence: Tutorial for Harnessing Electronic Health Records With Advanced Informatic Technologies.
Authors: Hou J, Zhao R, Gronsbell J, Lin Y, Bonzel CL, Zeng Q, Zhang S, Beaulieu-Jones BK, Weber GM, Jemielita T, Wan SS, Hong C, Cai T, Wen J, Ayakulangara Panickan V, Liaw KL, Liao K, Cai T.
J Med Internet Res
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ARCH: Large-scale Knowledge Graph via Aggregated Narrative Codified Health Records Analysis.
Authors: Gan Z, Zhou D, Rush E, Panickan VA, Ho YL, Ostrouchov G, Xu Z, Shen S, Xiong X, Greco KF, Hong C, Bonzel CL, Wen J, Costa L, Cai T, Begoli E, Xia Z, Gaziano JM, Liao KP, Cho K, Cai T, Lu J.
medRxiv
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Potential pitfalls in the use of real-world data for studying long COVID.
Authors: Zhang HG, Honerlaw JP, Maripuri M, Samayamuthu MJ, Beaulieu-Jones BR, Baig HS, L'Yi S, Ho YL, Morris M, Panickan VA, Wang X, Weber GM, Liao KP, Visweswaran S, Tan BWQ, Yuan W, Gehlenborg N, Muralidhar S, Ramoni RB, Kohane IS, Xia Z, Cho K, Cai T, Brat GA.
Nat Med
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Multimodal representation learning for predicting molecule-disease relations.
Authors: Wen J, Zhang X, Rush E, Panickan VA, Li X, Cai T, Zhou D, Ho YL, Costa L, Begoli E, Hong C, Gaziano JM, Cho K, Lu J, Liao KP, Zitnik M, Cai T.
Bioinformatics
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Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization.
Authors: Zhou D, Gan Z, Shi X, Patwari A, Rush E, Bonzel CL, Panickan VA, Hong C, Ho YL, Cai T, Costa L, Li X, Castro VM, Murphy SN, Brat G, Weber G, Avillach P, Gaziano JM, Cho K, Liao KP, Lu J, Cai T.
J Biomed Inform
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Scalable relevance ranking algorithm via semantic similarity assessment improves efficiency of medical chart review.
Authors: Cai T, He Z, Hong C, Zhang Y, Ho YL, Honerlaw J, Geva A, Ayakulangara Panickan V, King A, Gagnon DR, Gaziano M, Cho K, Liao K, Cai T.
J Biomed Inform
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Clinical knowledge extraction via sparse embedding regression (KESER) with multi-center large scale electronic health record data.
Authors: Hong C, Rush E, Liu M, Zhou D, Sun J, Sonabend A, Castro VM, Schubert P, Panickan VA, Cai T, Costa L, He Z, Link N, Hauser R, Gaziano JM, Murphy SN, Ostrouchov G, Ho YL, Begoli E, Lu J, Cho K, Liao KP, Cai T.
NPJ Digit Med
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A high-throughput phenotyping algorithm is portable from adult to pediatric populations.
Authors: Geva A, Liu M, Panickan VA, Avillach P, Cai T, Mandl KD.
J Am Med Inform Assoc
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