This paper contributes the first human-centered observational study of a deep learning system deployed directly in clinical care with patients. Through field observations and interviews at eleven clinics across Thailand, we explored the expectations and realities that nurses encounter in bringing a deep learning model into their clinical practices. First, we outline typical eye-screening workflows and challenges that nurses experience when screening hundreds of patients. Then, we explore the expectations nurses have for an AI-assisted eye screening process. Next, we present a human-centered, observational study of the deep learning system used in clinical care, examining nurses’ experiences with the system, and the socio-environmental factors that impacted system performance. Finally, we conclude with a discussion around applications of HCI methods to the evaluation of deep learning algorithms in clinical environments.
Publication to book
Las publicaciones que se encuentren en esta catergoría estarán incorporadas al libro “Los estados de la Inteligencia Artificial”.
Phyton’s most notable points are:
-Is a great library ecosystem (Scikit-learn, Pandas, Matplotlib, NLTK, Scikit-image, PyBrain, Caffe, StatsModels, TensorFlow, Keras, etc).
-Has a low entry barrier, has flexibility, is a platform independence, has readability, good visualization options, good community support and growing popularity.
The EU can become a leading role model for a society empowered by data to make better decisions -in business and the public sector. To fulfil this ambition, the EU can build on a strong legal framework – in terms of data protection, fundamental rights, safety and cybersecurity and its internal market with competitive companies of all sizes and varied industrial base.
In the period 2021-2027, the Commission will invest in a High Impact Project on European data spaces and federated cloud infrastructures.
The purpose of this White Paper is to set out policy options on how to achieve these objectives. It does not address the development and use of AI for military purposes.The Commission invites Member States, other European institutions, and all stakeholders, including industry, social partners, civil society organisations, researchers, the public in general and any interested party, to react to the options and to contribute to the Commission’s future decision-making in this domain.
Turing Natural Language Generation (T-NLG) is a 17 billion parameter language model by Microsoft that outperforms the state of the art on many downstream NLP tasks. We present a demo of the model, including its freeform generation, question answering, and summarization capabilities, to academics for feedback and research purposes.
Cybersecurity attacks are growing both in frequency and sophistication over the years. This increasing sophistication and complexity call for more advancement and continuous innovation in defensive strategies. Traditional methods of intrusion detection and deep packet inspection, while still largely used
and recommended, are no longer sufficient to meet the demands of growing security threats.