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Early detection of breast cancer combined with targeted therapy offers the best outcome for breast cancer patients. This volume deal with a wide range of new technical innovations for improving breast cancer detection, diagnosis and therapy. There is a special focus on improvements in mammographic image quality, image analysis, magnetic resonance imaging of the breast and molecular imaging. A chapter on targeted therapy explores the option of less radical postoperative therapy for women with early, screen-detected breast cancers.
The fourth edition of the Handbook of Human Factors and Ergonomics has been completely revised and updated. This includes all existing third edition chapters plus new chapters written to cover new areas. These include the following subjects: Managing low-back disorder risk in the workplace Online interactivity Neuroergonomics Office ergonomics Social networking HF&E in motor vehicle transportation User requirements Human factors and ergonomics in aviation Human factors in ambient intelligent environments As with the earlier editions, the main purpose of this handbook is to serve the needs of the human factors and ergonomics researchers, practitioners, and graduate students. Each chapter has a strong theory and scientific base, but is heavily focused on real world applications. As such, a significant number of case studies, examples, figures, and tables are included to aid in the understanding and application of the material covered.
In the definitive history of a twentieth-century public health disaster, Alan Derickson recounts how, for decades after methods of prevention were known, hundreds of thousands of American miners suffered and died from black lung, a respiratory illness caused by the inhalation of coal mine dust. The combined failure of government, medicine, and industry to halt the spread of this disease—and even to acknowledge its existence—resulted in a national tragedy, the effects of which are still being felt.The book begins in the late nineteenth century, when the disorders brought on by exposure to coal mine dust were first identified as components of a debilitating and distinctive illness. For several decades thereafter, coal miners' dust disease was accepted, in both lay and professional circles, as a major industrial disease. Derickson describes how after the turn of the century medical professionals and industry representatives worked to discredit and supplant knowledge about black lung, with such success that this disease ceased to be recognized. Many authorities maintained that breathing coal mine dust was actually beneficial to health.Derickson shows that activists ultimately forced society to overcome its complacency about this deadly and preventable disease. He chronicles the growth of an unprecedented movement—from the turn-of-the-century miners' union, to the social medicine activists in the mid-twentieth century, and the black lung insurgents of the late sixties—which eventually won landmark protections and compensation with the enactment of the Federal Coal Mine Health and Safety Act in 1969. An extraordinary work of scholarship, Black Lung exposes the enormous human cost of producing the energy source responsible for making the United States the world's preeminent industrial nation.
Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques. This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.