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- 검색키워드
- 저자 : John T. Schwartz (검색결과 3 건)
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Applications of Machine Learning Using Electronic Medical Records in Spine Surgery
John T. Schwartz,Michael Gao,Eric A. Geng,Kush S. Mody,Christopher M. Mikhail,Samuel K. Cho 대한척추신경외과학회 2019 Neurospine Vol.16 No.4
Developments in machine learning in recent years have precipitated a surge in research on the applications of artificial intelligence within medicine. Machine learning algorithms are beginning to impact medicine broadly, and the field of spine surgery is no exception. Electronic medical records are a key source of medical data that can be leveraged for the creation of clinically valuable machine learning algorithms. This review examines the current state of machine learning using electronic medical records as it applies to spine surgery. Studies across the electronic medical record data domains of imaging, text, and structured data are reviewed. Discussed applications include clinical prognostication, preoperative planning, diagnostics, and dynamic clinical assistance, among others. The limitations and future challenges for machine learning research using electronic medical records are also discussed.
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Cruz, Deu John M.,Bonotto, Rafaela M.,Gomes, Rafael G. B.,da Silva, Camila T.,Taniguchi, Juliana B.,No, Joo Hwan,Lombardot, Benoit,Schwartz, Olivier,Hansen, Michael A. E.,Freitas-Junior, Lucio H. Public Library of Science 2013 PLoS neglected tropical diseases Vol.7 No.10
<▼1><P>Chikungunya virus (CHIKV) is a mosquito-borne arthrogenic alphavirus that causes acute febrile illness in humans accompanied by joint pains and in many cases, persistent arthralgia lasting weeks to years. The re-emergence of CHIKV has resulted in numerous outbreaks in the eastern hemisphere, and threatens to expand in the foreseeable future. Unfortunately, no effective treatment is currently available. The present study reports the use of resazurin in a cell-based high-throughput assay, and an image-based high-content assay to identify and characterize inhibitors of CHIKV-infection in vitro. CHIKV is a highly cytopathic virus that rapidly kills infected cells. Thus, cell viability of HuH-7 cells infected with CHIKV in the presence of compounds was determined by measuring metabolic reduction of resazurin to identify inhibitors of CHIKV-associated cell death. A kinase inhibitor library of 4,000 compounds was screened against CHIKV infection of HuH-7 cells using the resazurin reduction assay, and the cell toxicity was also measured in non-infected cells. Seventy-two compounds showing ≥50% inhibition property against CHIKV at 10 µM were selected as primary hits. Four compounds having a benzofuran core scaffold (CND0335, CND0364, CND0366 and CND0415), one pyrrolopyridine (CND0545) and one thiazol-carboxamide (CND3514) inhibited CHIKV-associated cell death in a dose-dependent manner, with EC<SUB>50</SUB> values between 2.2 µM and 7.1 µM. Based on image analysis, these 6 hit compounds did not inhibit CHIKV replication in the host cell. However, CHIKV-infected cells manifested less prominent apoptotic blebs typical of CHIKV cytopathic effect compared with the control infection. Moreover, treatment with these compounds reduced viral titers in the medium of CHIKV-infected cells by up to 100-fold. In conclusion, this cell-based high-throughput screening assay using resazurin, combined with the image-based high content assay approach identified compounds against CHIKV having a novel antiviral activity - inhibition of virus-induced CPE - likely by targeting kinases involved in apoptosis.</P></▼1><▼2><P><B>Author Summary</B></P><P>Recent outbreaks and expanding global distribution of Chikungunya virus (CHIKV) in different regions of Asia, Africa and Europe necessitates the development of effective therapeutic interventions. At present, only two antiviral compounds (chloroquine and ribavirin) that inhibit viral infection <I>in vitro</I> have been used in clinical cases of chikungunya infections. However, neither of these compounds have shown strong efficacy in vivo. Recent attempts to identify new antiviral candidates for CHIKV using cell-based phenotypic approach have been reported. In this study, we developed a simple cell-based high-throughput assay using resazurin to identify potential anti-CHIKV compounds. This high-throughput assay is based on the metabolic reduction of resazurin to the highly fluorescent resorufin by viable cells as an indicator of activity against CHIKV-induced CPE. We screened 4,000 small molecules belonging to the BioFocus kinase inhibitor chemical library and found a cluster of related molecules with antiviral activity against CHIKV. Finally, we characterized the putative mode of action of these active compounds using an image-based high content assay and conventional virological methods (<I>i.e.</I>, virus yield reduction assay, microneutralization assay).</P></▼2>
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Emerging Technologies in the Treatment of Adult Spinal Deformity
Akshar V. Patel,Christopher A. White,John T. Schwartz,Nicholas L. Pitaro,Kush C. Shah,Sirjanhar Singh,Varun Arvind,Jun S. Kim,Samuel K. Cho 대한척추신경외과학회 2021 Neurospine Vol.18 No.3
Outcomes for adult spinal deformity continue to improve as new technologies become integrated into clinical practice. Machine learning, robot-guided spinal surgery, and patient-specific rods are tools that are being used to improve preoperative planning and patient satisfaction. Machine learning can be used to predict complications, readmissions, and generate postoperative radiographs which can be shown to patients to guide discussions about surgery. Robot-guided spinal surgery is a rapidly growing field showing signs of greater accuracy in screw placement during surgery. Patient-specific rods offer improved outcomes through higher correction rates and decreased rates of rod breakage while decreasing operative time. The objective of this review is to evaluate trends in the literature about machine learning, robot-guided spinal surgery, and patient-specific rods in the treatment of adult spinal deformity.
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