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Applications of Artificial Intelligence and Digital Holography in Biomedical Microscopy
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  • Anayet Ullah Dar,
  • Abdul Basit Ahanger,
  • Muzafar Rasool,
  • Mandeep Singh,
  • Assif Assad,
  • Muzafar Ahmad Macha,
  • Syed Wajid Aalam,
  • Abdul Nafi Ahanger
Anayet Ullah Dar
Islamic University of Science and Technology
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Abdul Basit Ahanger
Islamic University of Science and Technology
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Muzafar Rasool
Islamic University of Science and Technology

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Mandeep Singh
Islamic University of Science and Technology
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Assif Assad
Islamic University of Science and Technology
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Muzafar Ahmad Macha
Islamic University of Science and Technology
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Syed Wajid Aalam
Islamic University of Science and Technology
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Abdul Nafi Ahanger
Islamic University of Science and Technology
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Abstract

Digital holography (DH) has experienced significant advancements in recent years, with improvements in both experimental and algorithmic techniques. This has resulted in an expansion of DH’s applications in biomedicine, as well as other scientific and engineering fields. The introduction of machine learning (ML) and deep learning (DL) has provided a breakthrough in the recognition and prediction of patterns, especially with regards to visual imagery data. This characteristic of ML and DL makes them highly suitable for processing digital holographic data, and they have thus become widely used in digital holography. This review aims to assimilate the research where ML and DL have been employed alongside digital holography in the biomedical field for tasks such as the identification and classification of organelles, diseases, and microbes. The combination of DH and ML/DL has shown significant potential in addressing various challenges in biomedical microscopy, including the identification and classification of cellular and subcellular