[HTML][HTML] Artificial intelligence in hematological diagnostics: Game changer or gadget?
W Walter, C Pohlkamp, M Meggendorfer, N Nadarajah… - Blood Reviews, 2023 - Elsevier
The future of clinical diagnosis and treatment of hematologic diseases will inevitably involve
the integration of artificial intelligence (AI)-based systems into routine practice to support the …
the integration of artificial intelligence (AI)-based systems into routine practice to support the …
How artificial intelligence might disrupt diagnostics in hematology in the near future
W Walter, C Haferlach, N Nadarajah, I Schmidts… - Oncogene, 2021 - nature.com
Artificial intelligence (AI) is about to make itself indispensable in the health care sector.
Examples of successful applications or promising approaches range from the application of …
Examples of successful applications or promising approaches range from the application of …
Machine learning applications in the diagnosis of leukemia: Current trends and future directions
Abstract Machine learning (ML) offers opportunities to advance pathological diagnosis,
especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is …
especially with increasing trends in digitalizing microscopic images. Diagnosing leukemia is …
Prototype‐based models in machine learning
An overview is given of prototype‐based models in machine learning. In this framework,
observations, ie, data, are stored in terms of typical representatives. Together with a suitable …
observations, ie, data, are stored in terms of typical representatives. Together with a suitable …
Artificial intelligence and map** a new direction in laboratory medicine: a review
Background Modern artificial intelligence (AI) and machine learning (ML) methods are now
capable of completing tasks with performance characteristics that are comparable to those of …
capable of completing tasks with performance characteristics that are comparable to those of …
Application of machine learning in the management of acute myeloid leukemia: current practice and future prospects
Abstract Machine learning (ML) is rapidly emerging in several fields of cancer research. ML
algorithms can deal with vast amounts of medical data and provide a better understanding of …
algorithms can deal with vast amounts of medical data and provide a better understanding of …
Artificial intelligence and digital microscopy applications in diagnostic hematopathology
Digital Pathology is the process of converting histology glass slides to digital images using
sophisticated computerized technology to facilitate acquisition, evaluation, storage, and …
sophisticated computerized technology to facilitate acquisition, evaluation, storage, and …
Interactive online learning for obstacle classification on a mobile robot
We present an architecture for incremental online learning in high-dimensional feature
spaces and apply it on a mobile robot. The model is based on learning vector quantization …
spaces and apply it on a mobile robot. The model is based on learning vector quantization …
Aspects in classification learning-Review of recent developments in Learning Vector Quantization
Classification is one of the most frequent tasks in machine learning. However, the variety of
classification tasks as well as classifier methods is huge. Thus the question is coming up …
classification tasks as well as classifier methods is huge. Thus the question is coming up …
Machine learning and augmented human intelligence use in histomorphology for haematolymphoid disorders
Advances in digital pathology have allowed a number of opportunities such as decision
support using artificial intelligence (AI). The application of AI to digital pathology data shows …
support using artificial intelligence (AI). The application of AI to digital pathology data shows …