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1. |
Record Nr. |
UNINA9910702973803321 |
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Titolo |
Addressing the need for comprehensive regulatory reform [[electronic resource] ] : hearing before the Committee on Financial Services, U.S. House of Representatives, One Hundred Eleventh Congress, first session, March 26, 2009 |
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Pubbl/distr/stampa |
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Washington : , : U.S. G.P.O., , 2009 |
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Descrizione fisica |
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1 online resource (iii, 60 pages) |
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Soggetti |
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Financial services industry - Government policy - United States |
Financial institutions - Government policy - United States |
Trade regulation - United States |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from title screen (viewed on Nov. 9, 2009). |
Paper version available for sale by the Supt. of Docs., U.S. G.P.O. |
"Serial no. 111-22." |
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2. |
Record Nr. |
UNINA9910482988603321 |
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Titolo |
Advanced Machine Learning Approaches in Cancer Prognosis : Challenges and Applications / / edited by Janmenjoy Nayak, Margarita N. Favorskaya, Seema Jain, Bighnaraj Naik, Manohar Mishra |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2021 |
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ISBN |
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Edizione |
[1st ed. 2021.] |
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Descrizione fisica |
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1 online resource (461 pages) |
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Collana |
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Intelligent Systems Reference Library, , 1868-4408 ; ; 204 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Medicine - Research |
Biology - Research |
Machine learning |
Computational Intelligence |
Biomedical Research |
Machine Learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Advances in Machine Learning Approaches in Cancer Prognosis -- Data Analysis on Cancer Disease using Machine Learning Techniques -- Learning from multiple modalities of imaging data for cancer detection/diagnosis -- Neural Network for Lung Cancer diagnosis -- Improved Thyroid Disease Prediction Model Using Data Mining Techniques with Outlier Detection -- Automated Breast Cancer Diagnosis Based on Neural Network Algorithms. . |
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Sommario/riassunto |
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This book introduces a variety of advanced machine learning approaches covering the areas of neural networks, fuzzy logic, and hybrid intelligent systems for the determination and diagnosis of cancer. Moreover, the tactical solutions of machine learning have proved its vast range of significance and, provided novel solutions in the medical field for the diagnosis of disease. This book also explores the distinct deep learning approaches that are capable of yielding more accurate outcomes for the diagnosis of cancer. In addition to providing |
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an overview of the emerging machine and deep learning approaches, it also enlightens an insight on how to evaluate the efficiency and appropriateness of such techniques and analysis of cancer data used in the cancer diagnosis. Therefore, this book focuses on the recent advancements in the machine learning and deep learning approaches used in the diagnosis of different types of cancer along with their research challenges and future directions for the targeted audience including scientists, experts, Ph.D. students, postdocs, and anyone interested in the subjects discussed. . |
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3. |
Record Nr. |
UNINA9910133207003321 |
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Titolo |
Family advocate : a practical journal by the ABA Family Law Section |
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Pubbl/distr/stampa |
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Chicago, IL, : Section of Family Law, American Bar Association, ©1978- |
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ISSN |
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Disciplina |
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Soggetti |
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Domestic relations - United States |
Family |
Legislation as Topic |
Familles - Droit - États-Unis |
Prawo rodzinne |
Domestic relations |
Periodical |
Czasopismo prawnicze |
Periodicals. |
Stany Zjednoczone |
United States |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Periodico |
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