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ANNOTATED BIBLIOGRAPHY
Kim, B. W., Cho, H., Choi, C. H., Ylaya, K., Chung, J.-Y., Kim, J.-H., & Hewitt, S. M. (2015). Clinical significance of OCT4 and SOX2 protein expression in cervical cancer. BMC Cancer, 15, 1015. https://doi.org/10.1186/s12885-015-2015-1
The authors critically evaluate the significance of SOX2 and OCT4 in the framework of cancer stem cells which were present in certain solid tumors. The methodology pursued the experiment with immunohistochemistry for OCT4 and SOX2 on 289 cervical intraepithelial neoplasia sections, 305 cervical epithelium samples and 161 cervical cancers in comparison to samples with clinicopathologic elements. The study concluded with the results that OCT4 overexpression and loss of SOX2 are strongly linked with the poor prognosis of cervical cancer.
Lee, C. H., & Yoon, H.-J. (2017). Medical big data: promise and challenges. Kidney Research and Clinical Practice, 36(1), 3–11. https://doi.org/10.23876/j.krcp.2017.36.1.3
The authors highlight the widespread manifestations of bog data. The medical big data analysis comprises several features which are not only distinct from other disciplines but also unique from the traditional practices of clinical epidemiology. In addition, the techniques and implications of big data are explicated to as safety or disease surveillance, clinical decision support, predictive modeling, research and public health. However, technical issues as bias control and missing values limit the scope of the studies and the outcome.
Lehmann, C. U., & Technology, C. on C. I. (2015). Pediatric Aspects of Inpatient Health Information Technology Systems. Pediatrics, 135(3), e756–e768. https://doi.org/10.1542/peds.2014-4148
The report manifests the extensive studies based on the last three years of the Health Information Technology for Economic and Clinical Health Act. The program enhanced the adoption of electronic health records (EHRs) with hospitals and providers to leverage incentives pertinent to meaningful use. The report underpins the technical pediatric-specific concepts, required functionalities in clinical information systems and the needs and data of child health. The future implications are also deliberated where pediatricians ought to lobby for enhancement of the inpatient HIT systems to improve the tendency to support efficient and safe delivery for children.
Li, X.-P., Zhang, X.-W., Zheng, L.-Z., & Guo, W.-J. (2015). Expression of CD44 in pancreatic cancer and its significance. International Journal of Clinical and Experimental Pathology, 8(6), 6724–6731.
The research study deliberates the therapeutic target CD44 involved in pancreatic cancer. The significance of CD44 in pancreatic cancer and the correlation with the diagnosis of pancreatic cancer is examined. The study collected samples of sixty-seven pancreatic cancer samples in a hospital associated with Shanghai Jiaotong University. In addition to getting the clinical data of patients, age, location, history, gender, lymph node metastasis and location were noted. The results concluded that the positive rates of CD44 expression accounted for 73.1% in the pancreatic samples. The bottom line is that CD44 was critically related to the aggressive malignant and distant metastasis behaviors of pancreatic cancer.
McCullough, J. S., Parente, S. T., & Town, R. (2016). Health information technology and patient outcomes: The role of information and labor coordination. RAND Journal of Economics, 47(1), 207–236. https://doi.org/10.1111/1756-2171.12124
The research study highlights the manifestations and competence of Health Information technology (IT). In the study, the impacts of the adoption of hospital IT on patient outcomes and the organizational heterogeneity are explicated. A critical appraisal of the inspection reveals that the adoption of health IT reduces the mortality for the most critical patients but refrains from casting any impact on the median patient. Primarily, the benefits of health IT are harnessed by those whose diagnosis requires extensive clinical information system and cross-specialty care coordination.
Mennemeyer, S. T., Menachemi, N., Rahurkar, S., & Ford, E. W. (2016). Impact of the HITECH Act on physicians’ adoption of electronic health records. Journal of the American Medical Informatics Association: JAMIA, 23(2), 375–379. https://doi.org/10.1093/jamia/ocv103
The research study highlights the meaningful use (MU) programs that ultimately aimed at enhancing healthcare outcomes. The essence of the study evaluates the extent to which the MU program influenced the EHR adoption curve which existed before the Act. The bottom line is that authors found weak evidence of the significance of the MU initiative on HER uptake.
Miller, D. D., & Brown, E. W. (2018). Artificial Intelligence in Medical Practice: The Question to the Answer? The American Journal of Medicine, 131(2), 129–133. https://doi.org/10.1016/j.amjmed.2017.10.035
Artificial intelligence plays an instrumental role in every walk of life and similar patterns are observed in the medical practice. However, the definite answer to the intriguing extent that to what extent AI an impact medical practice remains undressed. In pathology, radiology and dermatology, AI is being cultivated for processing image analysis. It is stipulated that AI can optimize the trajectory of chronic diseases and medical errors.
References
ADDIN ZOTERO_BIBL {"uncited":[],"omitted":[],"custom":[]} CSL_BIBLIOGRAPHY Kim, B. W., Cho, H., Choi, C. H., Ylaya, K., Chung, J.-Y., Kim, J.-H., & Hewitt, S. M. (2015). Clinical significance of OCT4 and SOX2 protein expression in cervical cancer. BMC Cancer, 15, 1015. https://doi.org/10.1186/s12885-015-2015-1
Lee, C. H., & Yoon, H.-J. (2017). Medical big data: promise and challenges. Kidney Research and Clinical Practice, 36(1), 3–11. https://doi.org/10.23876/j.krcp.2017.36.1.3
Lehmann, C. U., & Technology, C. on C. I. (2015). Pediatric Aspects of Inpatient Health Information Technology Systems. Pediatrics, 135(3), e756–e768. https://doi.org/10.1542/peds.2014-4148
Li, X.-P., Zhang, X.-W., Zheng, L.-Z., & Guo, W.-J. (2015). Expression of CD44 in pancreatic cancer and its significance. International Journal of Clinical and Experimental Pathology, 8(6), 6724–6731.
McCullough, J. S., Parente, S. T., & Town, R. (2016). Health information technology and patient outcomes: The role of information and labor coordination. RAND Journal of Economics, 47(1), 207–236. https://doi.org/10.1111/1756-2171.12124
Mennemeyer, S. T., Menachemi, N., Rahurkar, S., & Ford, E. W. (2016). Impact of the HITECH Act on physicians’ adoption of electronic health records. Journal of the American Medical Informatics Association: JAMIA, 23(2), 375–379. https://doi.org/10.1093/jamia/ocv103
Miller, D. D., & Brown, E. W. (2018). Artificial Intelligence in Medical Practice: The Question to the Answer? The American Journal of Medicine, 131(2), 129–133. https://doi.org/10.1016/j.amjmed.2017.10.035
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