Artificial intelligence for digital and computational pathology
Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …
including deep learning, have boosted the field of computational pathology. This field holds …
AI in pathology: what could possibly go wrong?
The field of medicine is undergoing rapid digital transformation. Pathologists are now
striving to digitize their data, workflows, and interpretations, assisted by the enabling …
striving to digitize their data, workflows, and interpretations, assisted by the enabling …
[HTML][HTML] Federated benchmarking of medical artificial intelligence with MedPerf
A Karargyris, R Umeton, MJ Sheller… - Nature machine …, 2023 - nature.com
Medical artificial intelligence (AI) has tremendous potential to advance healthcare by
supporting and contributing to the evidence-based practice of medicine, personalizing …
supporting and contributing to the evidence-based practice of medicine, personalizing …
How will generative AI disrupt data science in drug discovery?
JP Vert - Nature Biotechnology, 2023 - nature.com
In the short few months since the release of ChatGPT 1, 2, the potential for large language
models (LLMs) and generative artificial intelligence (AI) to disrupt fields as diverse as art …
models (LLMs) and generative artificial intelligence (AI) to disrupt fields as diverse as art …
[HTML][HTML] Collaborative and privacy-preserving retired battery sorting for profitable direct recycling via federated machine learning
Unsorted retired batteries with varied cathode materials hinder the adoption of direct
recycling due to their cathode-specific nature. The surge in retired batteries necessitates …
recycling due to their cathode-specific nature. The surge in retired batteries necessitates …
Federated learning for medical image analysis: A survey
Abstract Machine learning in medical imaging often faces a fundamental dilemma, namely,
the small sample size problem. Many recent studies suggest using multi-domain data …
the small sample size problem. Many recent studies suggest using multi-domain data …
One label is all you need: Interpretable AI-enhanced histopathology for oncology
Artificial Intelligence (AI)-enhanced histopathology presents unprecedented opportunities to
benefit oncology through interpretable methods that require only one overall label per …
benefit oncology through interpretable methods that require only one overall label per …
Application of digital pathology‐based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response
In recent years, the application of advanced analytics, especially artificial intelligence (AI), to
digital H&E images, and other histological image types, has begun to radically change how …
digital H&E images, and other histological image types, has begun to radically change how …
[HTML][HTML] Artificial intelligence in neuro-oncology: advances and challenges in brain tumor diagnosis, prognosis, and precision treatment
This review delves into the most recent advancements in applying artificial intelligence (AI)
within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors …
within neuro-oncology, specifically emphasizing work on gliomas, a class of brain tumors …
Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions
Artificial intelligence (AI) in oncology is advancing beyond algorithm development to
integration into clinical practice. This review describes the current state of the field, with a …
integration into clinical practice. This review describes the current state of the field, with a …