Informasi Umum

Kode

21.21.1899

Klasifikasi

610.28 - Biomedical Engineering

Jenis

Buku - Elektronik (E-Book)

Subjek

Biomedical Engineering

No. Rak

11b

Dilihat

82 kali

Informasi Lainnya

Abstraksi

Deep learning (DL) is a method of machine learning, running over artificial neural networks, that uses multiple layers to extract high-level features from large amounts of raw data. DL methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications gives readers a complete overview of the essential concepts of DL and its applications in the field of biomedical engineering. DL has been rapidly developed in recent years, in terms of both methodological constructs and practical applications. DL provides computational models of multiple processing layers to learn and represent data with higher levels of abstraction. It is able to implicitly capture intricate structures of large-scale data and is ideally suited to many of the hardware architectures that are currently available. The ever-expanding amount of data that can be gathered through biomedical and clinical information sensing devices necessitates the development of machine learning and artificial intelligence techniques such as DL and convolutional neural networks to process and evaluate the data. Some examples of biomedical and clinical sensing devices that use DL include computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic particle imaging, electroencephalography/magnetoencephalography (EE/MEG), optical microscopy and tomography, photoacoustic tomography, electron tomography, and atomic force microscopy. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications provides the most complete coverage of DL applications in biomedical engineering available, including detailed real-world applications in areas such as computational neuroscience, neuroimaging, data fusion, medical image processing, neurological disorder diagnosis for diseases such as Alzheimer’s, attention deficit hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), tumor prediction, and translational multimodal imaging analysis.

  • TEI7D3 - TOPIK LANJUT DALAM INSTRUMENTASI DAN PENGOLAHAN SINYAL BIOMEDIS

Koleksi & Sirkulasi

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Pengarang

Nama Valentina Balas, Brojo Mishra, Raghvendra Kumar
Jenis Perorangan
Penyunting
Penerjemah

Penerbit

Nama Elsevier
Kota New York
Tahun 2021

Sirkulasi

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Denda harian IDR 0,00
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