Dr. L. Santiago Medina M.D., MPH, Dr. C. Craig Blackmore's Evidence-Based Neuroimaging Diagnosis and Treatment: PDF

Diagnosis

By Dr. L. Santiago Medina M.D., MPH, Dr. C. Craig Blackmore M.D., MPH (auth.), L. Santiago Medina, Pina C. Sanelli, Jeffrey G. Jarvik (eds.)

Evidence-Based Neuroimaging is a elementary consultant that employs evidence-based medication standards to systematically assessment the proof defining the right use of clinical imaging for the mind, backbone, head, and neck. Edited through L. Santiago Medina, Pina C. Sanelli, and Jeffrey G. Jarvik, the publication presents a scientific framework for knowing the easiest imaging offerings for sufferer care. Chapters spotlight key issues that aid medical functions, permitting quickly entry to pertinent details together with sufferer choice, imaging thoughts, attempt functionality, cost-effectiveness, and applicability. The diagnostic imaging of many universal ailments, problems, and stipulations are lined, together with a number of sclerosis, acute ischemic stroke, dementia, Alzheimer’s disorder, stressful mind damage, autism, spinal trauma, spinal infections, neck plenty, thyroid melanoma, and cervical lymph node metastasis. by means of delivering a transparent knowing of the technology at the back of the facts, the publication fills a void for radiologists, neurologists, neurosurgeons, pediatricians, basic care physicians, and different clinicians with an curiosity in neuroimaging and a wish to enforce an evidence-based strategy into their day-by-day practice.

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JAMA. 1994;271:703–7. 39. Malone D. Radiology. 2007;242(1):12–4. 2 Assessing the Imaging Literature: Understanding Error and Bias C. Craig Blackmore, L. Santiago Medina, James G. Ravenel, Gerard A. Silvestri, and Kimberly E. Applegate Contents Discussion of Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Are Error and Bias? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What Is Random Error?

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Conversely, the specificity with a low threshold is less than the specificity with a high threshold (Fig. 1b) [14, 15]. The positive predictive value is defined as the probability that a patient will have a disease given that the patient’s test is positive. In other words, when a group of patients test positive, we want to know how frequently they will have the disease. The formula for the positive predictive value (PPV) is provided in the table in Appendix 1. Similarly, the negative 1 Evidence-Based Imaging: Principles 9 Fig.

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