Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Prior-Informed Learning Techniques for Macroscopic and Microscopic Imaging Biomarker Identification

Prior-Informed Learning Techniques for Macroscopic and Microscopic Imaging Biomarker Identification

Muhlberg, Alexander

Paperback

Medical ReferenceGeneral Computers

PREORDER - Expected ship date August 31, 2027

ISBN10: 3832557156
ISBN13: 9783832557157
Publisher: Logos Verlag Berlin
Published: Aug 31 2027
Pages: 140
Weight: 0.72
Language: English
Based on the success of artificial intelligence (AI), its use for automated diagnostics of medical image data has become a major focus. Despite excellent results on prediction tasks involving big data, a naive application of deep learning, i.e., without any prior knowledge of the domain, may not be the optimal solution when there are only small amounts of data for the prediction task at hand. This, however, is often the case in clinical studies and biological experiments. Therefore, it may be beneficial to integrate prior information into the learning technique. With that in mind, this book identifies novel macroscopic and microscopic imaging biomarkers for computed tomography and multiphoton microscopy by developing image processing and prior-informed learning techniques for research in pulmonology, oncology, and myology. A spectrum of learning methods is explored, ranging from the traditional, i.e., statistics or classical machine learning with handcrafted features, to the modern, i.e., deep learning and meta-learning, resulting in novel hybrid biomarker systems that seamlessly blend prior knowledge with the power of AI.

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