Plunkett's Artificial Intelligence (ai) & Machine Learning Industry Almanac

Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field

Over the past decade, Artificial Intelligence has proved invaluable in a range of industry verticals such as automotive and assembly, life sciences, retail, oil and gas, and travel. The leading sectors adopting AI rapidly are Financial Services, Automotive and Assembly, High Tech and Telecommunications. Travel has been slow in adoption, but the opportunity for generating incremental value by leveraging AI to augment traditional analytics driven solutions is extremely high.

Artificial Intelligence (AI) with Python Machine Learning and Python Deep Learning, Transfer Learning, Tensorflow

In recent years, AI/ML tools have become more prevalent in the fields of medical imaging and imaging informatics, where systems are already outperforming physicians in a range of domains, such as in the classification of retinal fundus images in ophthalmology, chest X-rays in radiology, and skin cancer detection in dermatology, among many others. It has recently emerged as one of the fastest growing research areas given the evolution of techniques in radiology, molecular imaging, anatomical imaging, and functional imaging for detection, segmentation, diagnosis, annotation, summarization, and prediction. The ongoing innovations in this exciting and promising field play a powerful role in influencing the lives of millions through health, safety, education, and other opportunities intended to be shared across all segments of society. To achieve further progress, this Special Issue (SI) invited both research and review-type manuscripts to showcase ongoing research progress and development based on applications of AI/ML (especially DL techniques) in medical imaging to influence human health and healthcare systems in the diagnostic decision-making process. The SI published fourteen articles after a rigorous peer-review process across the spectrum of medical imaging modalities and the diversity of specialties depending on imaging techniques from radiology, dermatology, pathology, colonoscopy, endoscopy, etc.