Winner of the Computer History Museum Prize of the Special Interest Group: Computers, Information, and Society Imagine biology and medicine today without computers. What would laboratory work be like if electronic databases and statistical software did not exist? Would disciplines like genomics even be feasible if we lacked the means to manage and manipulate huge volumes of digital data? How would patients fare in a world absent CT scans, programmable pacemakers, and computerized medical records? Today, computers are a critical component of almost all research in biology and medicine. Yet, just fifty years ago, the study of life was by far the least digitized field of science, its living subject matter thought too complex and dynamic to be meaningfully analyzed by logic-driven computers. In this long-overdue study, historian Joseph November explores the early attempts, in the 1950s and 1960s, to computerize biomedical research in the United States. Computers and biomedical research are now so intimately connected that it is difficult to imagine when such critical work was offline. Biomedical Computing transports readers back to such a time and investigates how computers first appeared in the research lab and doctor's office. November examines the conditions that made possible the computerization of biology—including strong technological, institutional, and political support from the National Institutes of Health—and shows not only how digital technology transformed the life sciences but also how the intersection of the two led to important developments in computer architecture and software design. The history of this phenomenon has been only vaguely understood. November's thoroughly researched and lively study makes clear for readers the motives behind computerizing the study of life and how that technology profoundly affects biomedical research today.

Despite success with treatment when diagnosed early, breast cancer is still one of the most fatal forms of cancer for women. Imaging diagnosis is still one of the most efficient ways to detect early breast changes with mammography among the most used techniques. However, there are other techniques that have emerged as alternatives or even complementary tests in the early detection of breast lesions (e.g., breast thermography and electrical impedance tomography). Artificial intelligence can be used to optimize image diagnosis, increasing the reliability of the reports and supporting professionals who do not have enough knowledge or experience to make good diagnoses. Biomedical Computing for Breast Cancer Detection and Diagnosis is a collection of research that presents a review of the physiology and anatomy of the breast; the dynamics of breast cancer; principles of pattern recognition, artificial neural networks, and computer graphics; and the breast imaging techniques and computational methods to support and optimize the diagnosis. While highlighting topics including mammograms, thermographic imaging, and intelligent systems, this book is ideally designed for medical oncologists, surgeons, biomedical engineers, medical imaging professionals, cancer researchers, academicians, and students in medicine, biomedicine, biomedical engineering, and computer science.

Presents an up-to-date review of the application of image-directed neurosurgery of brain tumours, a process now accepted as being far safer and more accurate than earlier methods. The book includes such recent advances as frameless stereotactic techniques and the use of robotics.