Lilhore Umesh Kumar Anand Abhineet (16 results)

Condition: New.

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Paperback. Condition: new. Paperback. Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management. It also benefits data scientists, engineers, policymakers, and professionals in the pharmaceutical and biotechnology industries. Graduate students interested in healthcare and technology will find accessible information on the latest developments in AI-driven approaches to AD detection and prediction. "This book is the culmination of our collaborative efforts, bringing together expertise from various disciplines, including artificial intelligence, computer science, neuroscience, and healthcare. Our shared goal is to address the pressing challenges posed by Alzheimer's disease through innovative AI-driven solutions"-- Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: As New. Unread book in perfect condition.

Condition: New.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: new. Paperback. Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management. It also benefits data scientists, engineers, policymakers, and professionals in the pharmaceutical and biotechnology industries. Graduate students interested in healthcare and technology will find accessible information on the latest developments in AI-driven approaches to AD detection and prediction. "This book is the culmination of our collaborative efforts, bringing together expertise from various disciplines, including artificial intelligence, computer science, neuroscience, and healthcare. Our shared goal is to address the pressing challenges posed by Alzheimer's disease through innovative AI-driven solutions"-- Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: New. In.

Paperback. Condition: new. Paperback. Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management. It also benefits data scientists, engineers, policymakers, and professionals in the pharmaceutical and biotechnology industries. Graduate students interested in healthcare and technology will find accessible information on the latest developments in AI-driven approaches to AD detection and prediction. "This book is the culmination of our collaborative efforts, bringing together expertise from various disciplines, including artificial intelligence, computer science, neuroscience, and healthcare. Our shared goal is to address the pressing challenges posed by Alzheimer's disease through innovative AI-driven solutions"-- Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Condition: New.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: new. Hardcover. Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management. It also benefits data scientists, engineers, policymakers, and professionals in the pharmaceutical and biotechnology industries. Graduate students interested in healthcare and technology will find accessible information on the latest developments in AI-driven approaches to AD detection and prediction. Offers a groundbreaking solution to the significant challenges posed by Alzheimers disease (AD) by leveraging advanced AI techniques to enhance early diagnosis and prediction. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: As New. Unread book in perfect condition.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Alzheimer's disease (AD) poses a significant global health challenge, with an estimated 50 million people affected worldwide and no known cure. Traditional methods of diagnosis and prediction often rely on subjective assessments. They are limited in detecting the disease early, leading to delayed intervention and poorer patient outcomes. Additionally, the complexity of AD, with its multifactorial etiology and diverse clinical manifestations, requires a multidisciplinary approach for effective management. AI-Driven Alzheimer's Disease Detection and Prediction offers a groundbreaking solution by leveraging advanced artificial intelligence (AI) techniques to enhance early diagnosis and prediction of AD. This edited book provides a comprehensive overview of state-of-the-art research, methodologies, and applications at the intersection of AI and AD detection. By bridging the gap between traditional diagnostic methods and cutting-edge technology, this book facilitates knowledge exchange, fosters interdisciplinary collaboration, and contributes to innovative solutions for AD management.