Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.

Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions.

As with the actual practices of speech-language pathologists and audiologists, clinical education and supervision practices work best when they are grounded not only in concept and theory but also in research. Designed to act as a complete guide to both the theory and the research, The Clinical Education and Supervisory Process in Speech-Language Pathology and Audiology provides the most up-to-date information on these crucial topics. Following in the footsteps of their mentor, Jean Anderson, Drs. Elizabeth McCrea and Judith Brasseur have taken on the task of assembling important current research and best practices in clinical education and supervision into one comprehensive resource. With their prestigious team of contributing authors, this text represents the culmination of decades of study and real-world best practices. The Clinical Education and Supervisory Process in Speech-Language Pathology and Audiology covers clinical education and supervision across five unique constituent groups: clinical educators of graduate students, preceptors of audiology externs, mentors of clinical fellows, supervisors of support personnel, and supervisors of professionals transitioning between work settings. It also includes the latest information on certification and accreditation requirements for preparation in supervision. Topics include Foundations: Anderson’s Continuum of Supervision Components of the Process Expectations for Supervision Practical Research in Supervision Literature from other Disciplines Obtaining Feedback About the Supervisory Process The Ethics of Clinical Education and Supervision Supervisor Self-Study and Accountability Interprofessional Education and Practice in Clinical Education and Supervision Chapter appendices add numerous ancillary materials, allowing readers to easily adopt the most successful processes and strategies the research has revealed. Sample scripts of supervisory conferences, self-assessment tools, action plan tools, and analysis systems can all be found inside. The Clinical Education and Supervisory Process in Speech-Language Pathology and Audiology is intended as a primary resource for anyone in those professions in any setting who is engaged in the process of clinical education and supervision. With this text as their guide, clinical educators and supervisors will be able to ground their practices in the vast compiled research and study contained within.

This book is open access under a CC BY 4.0 license. This volume describes and explains the educational method of Case-Based Clinical Reasoning (CBCR) used successfully in medical schools to prepare students to think like doctors before they enter the clinical arena and become engaged in patient care. Although this approach poses the paradoxical problem of a lack of clinical experience that is so essential for building proficiency in clinical reasoning, CBCR is built on the premise that solving clinical problems involves the ability to reason about disease processes. This requires knowledge of anatomy and the working and pathology of organ systems, as well as the ability to regard patient problems as patterns and compare them with instances of illness scripts of patients the clinician has seen in the past and stored in memory. CBCR stimulates the development of early, rudimentary illness scripts through elaboration and systematic discussion of the courses of action from the initial presentation of the patient to the final steps of clinical management. The book combines general backgrounds of clinical reasoning education and assessment with a detailed elaboration of the CBCR method for application in any medical curriculum, either as a mandatory or as an elective course. It consists of three parts: a general introduction to clinical reasoning education, application of the CBCR method, and cases that can used by educators to try out this method.

Offering a practical, six-step approach to effective survey design, delivery, and analysis, Survey Methods for Medical and Health Professions Education provides a real-world framework for successful research and evaluation using surveys. Focused on medical and other health professional education research, this unique text features quick-reference checklists, high-yield explanations, and case examples throughout, making it both a foundational reference and a go-to resource for all health professions educators and researchers who use surveys. Provides a detailed and practical discussion of the steps in survey methodology, along with just enough theory to inform common decisions. Includes numerous real-world examples, both simple and complex, covering the wide range of problems researchers are likely to face. Addresses issues of survey fatigue and addresses the challenge of how to get "good data." Features "Voice of Experience" boxes—pearls based on authors’ actual experiences. Concludes each chapter with a checklist so readers can quickly ensure they have covered every necessary step of survey design and implementation. Contains a convenient glossary of terms. Offers guidance from expert international contributors in medical and health professions research. Summarizes the most current standards and understanding of survey research so that experienced and novice researchers alike can directly apply content to improve research rigor.