Surgical Robotics: Systems Applications and Visions Review

Average Reviews:

(More customer reviews)This book is great collection and well arranged. Most chapters were collected from SCI/EI papers. Even you had read some books before, I still recommended it. And though there is some mathematics, difficult to me, I think the study results within this book is very useful for clinical surgeon.
The advantage and disadvantage of some chapter:
Chapter 2-4: clear explain the developing history; except Chapter 4.6.2.7-8 lacks of detail financial report.
Chapter 5: It may be not interest by surgeon, because it may be solved by image analysis.
Chapter 6: It did not explain the NOTES, and that may disturbs the biomedical engineer. I think the problems to NOTES is that it lacks the well-designed curved instrument, not the robotcs.
Chapter 9: It explain very clear about the history of da Vinci System, but lack of detail of kinetic/kinematic/haptic-feedback details
Chapter 14: It did not mention the major problem of the electric power. The problem to capsule is the short time of electric power supply, not the imaging transfer or others. And according to the battery technique now, it seems impossible to be solved.
Chapter 18.4-5: useless, because surgeon have no time to check another video about tie tightness during busy surgery.
Chapter 20: useless, because the metastatic lymph node identification is more important than tumor, in surgical procedure.
Chapter 24 about tissue damage, 25 about surgical skills: recommended. Even you are a laparoscopic surgeon, and not interesting in robotic surgery; I still recommended.
Of course I am not a cardiac surgery, neurosurgery, orthopedics, and skipped about those chapter. I still suggested that every surgical department in any hospital should got this book.


Click Here to see more reviews about: Surgical Robotics: Systems Applications and Visions

Get 28% OFF

Click here for more information about Surgical Robotics: Systems Applications and Visions

Read More...

The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical Science Series) Review

Average Reviews:

(More customer reviews)With the increase in cancer trials both in medical research and the pharmaceutical industry, medical diagnostic tests including medical imaging evaluations are being used more and more. There is a need for adjudication when radiologists disagree on a diagnosis and some standard statistical measures from other fields are finding new application.
This book provides a thorough background on the subject, the methodology and the applications. It is very clearly written and not overly technical. The methodology is the classical frequentist approach to statistical inference. Recently, Lyle Broemeling has published a book on this topic that takes exclusively the Bayesian approach and explains the Bayesian approach for those who are not acquainted with it. When dealing with predictions based on evolving data the Bayesian approach might be more natural. This would be the case in a clinical trial where the data is reviewed sequentially.
A particularly important part of diagnostic accuracy analysis is the area under the ROC curve. Pepe does an excellent job of covering that topic. This text is referenced often in Broemeling's book since it provides an excellent explanation of the same topics using the frequentist approach that he covers with the Bayesian approach.

Click Here to see more reviews about: The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical Science Series)

This book describes statistical concepts and techniques for evaluating medical diagnostic tests and biomarkers for detecting disease. More generally, the techniques pertain to the statistical classification problem for predicting a dichotomous outcome. Measures for quantifying test accuracy are described including sensitivity, specificity, predictive values, diagnostic likelihood ratios and the Receiver Operating Characteristic Curve that is commonly used for continuous and ordinal valued tests. Statistical procedures are presented for estimating and comparing them. Regression frameworks for assessing factors that influence test accuracy and for comparing tests while adjusting for such factors are presented. This book presents many worked examples of real data and should be of interest to practicing statisticians or quantitative researchers involved in the development of tests for classification or prediction in medicine.

Click here for more information about The Statistical Evaluation of Medical Tests for Classification and Prediction (Oxford Statistical Science Series)

Read More...