Ortale (17 results)

Paperback. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

paperback. Condition: Good.

Paperback. Condition: Very Good. First Edition. Nineteen short stories; Karen Horn, Samantha Dunn, Lisa Teasley, liz gonzalez, Rochelle Low, Jody Hauber, and Mary Rakow each signed the title pages of their respective stories, each adding an inscription to a well-known novelist and winner of the Women's Prize in fiction. Crisp, clean pages; the soft cover has a very small wrinkle at the spine heel and a little chipping at the bottom right front corner, otherwise excellent.; 272 pp; Signed by All Authors.

Softcover. Condition: Near Fine. First Edition; First Printing. Signed by Samantha Dunn, Mary Rakow, Rochelle Low, Karen Horn, Jody Hauber, Lisa Teasley, Rachel Resnick, liz gonzalez, Rachel Resnick, Janet Fitch and Aimee Bender. A collection of short fiction by a diverse array of authors. ; 272 pages; Signed by Author.

Condition: Nuevo. 326 p.

Condition: Buone. italiano Condizioni dell'esterno: Buone Condizioni dell'interno: Buone.

RUSTICA. Condition: Libro nuevo. *El contenido de este libro, basado en datos censales y en información obtenida a través de entrevistas, tiene como eje de indagación las estrategias familiares de reproducción en un barrio pobre de la ciudad de La Plata, que los autores han denominado Barrio Esperanza. 264p.

Condition: Buone. Condizioni dell'esterno: Discrete con difetti, segni d'uso Condizioni dell'interno: Buone.

brossura. Condition: OTTIMO. CM. 15.5X21.5, PP. 106 CON FOTOGRAFIE A COLORI E IN B.N., SCHIZZI, SCHEMI ETC. LEGATO IN CARTONCINO MORBIDO.

Condition: New.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an in-depth analysis of cutting-edge research on healthcare applications of explainable machine intelligence. It showcases an array of the most recent findings, applications, and empirical results, utilizing advanced approaches for effective and trustworthy analysis and diagnosis across multiple medical fields. Key areas are reviewed, with further investigation into challenges, perspectives, emerging trends, and opportunities. The transformative potential of explainable machine intelligence is revealed in reshaping the landscape of healthcare through the implementation of transparent and trustworthy approaches.Explainable Machine Intelligence in Healthcareoffers valuable insights into the design, development, integration, and deployment of machine intelligence in healthcare delivery and patient care. It caters to a broad readership encompassing diverse stakeholders, such as academicians, researchers, scholars, instructors, practitioners, students, industry professionals, public health agencies, and NGOs.

Condition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.

Condition: new. Questo è un articolo print on demand.

Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides an in-depth analysis of cutting-edge research on healthcare applications of explainable machine intelligence. It showcases an array of the most recent findings, applications, and empirical results, utilizing advanced approaches for effective and trustworthy analysis and diagnosis across multiple medical fields. Key areas are reviewed, with further investigation into challenges, perspectives, emerging trends, and opportunities. The transformative potential of explainable machine intelligence is revealed in reshaping the landscape of healthcare through the implementation of transparent and trustworthy approaches.Explainable Machine Intelligence in Healthcareoffers valuable insights into the design, development, integration, and deployment of machine intelligence in healthcare delivery and patient care. It caters to a broad readership encompassing diverse stakeholders, such as academicians, researchers, scholars, instructors, practitioners, students, industry professionals, public health agencies, and NGOs 200 pp. Englisch.

Condition: New. Print on Demand.

Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Demystifying Healthcare AI: The Role of Explainable AI in Enhancing Clinical Decision Support.- Supporting Healthcare Decision-Making: A Journey through CDSS, Explainability, and Bias Mitigation with Explainable AI.- Designing a LLM-based Methodology for Assisting Physicians in Complex Clinical Data Interpretation.- Enhancing Decision Support in Healthcare with Explainable AI Models.- Improving Explanation Measures Inside the Decision-Making Process to Increase the Potential of AI Applications in Healthcare.- Batch Integrated Gradients: A Library for Explaining Temporal Electronic Health Records.- Embeddings and Domain Knowledge for Grounded Interpretable Sleep Staging.- Explainability-Enhanced Neural Network for Thoracic Diagnosis Improvement.- Decision Tree Models to Select High Risk Patients for Lung Cancer Screening and Model Interpretability.- Interpreting Convolutional Neural Networks for Brain Tumors: A Transparent Box Approach.- Explainable Artificial Intelligence for Melanoma Detection.- Shedding Light Inside the Black Box: Techniques for Explainable Artificial Intelligence in Healthcare.- Detection of Frontotemporal Dementia using an Interpretable Machine Learning Approach.- Evaluation of Explainability Methods in Medical Image Analysis.- Unveiling the Synergy of Explainable AI and Advanced Computational Techniques in Tuberculosis Detection.- Explainable AI in Healthcare: A Pathway to Trust and Regulatory Compliance.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 212 pp. Englisch.

Condition: New. PRINT ON DEMAND.