| 1. |
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
|
|
| 5. |
|
|
| 6. |
- Tschandl, P., et al.
(författare)
-
Human-computer collaboration for skin cancer recognition
- 2020
-
Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 26, s. 1229-1234
-
Tidskriftsartikel (refereegranskat)abstract
- The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent achievements in the accuracy of image-based AI for skin cancer diagnosis to address the effects of varied representations of AI-based support across different levels of clinical expertise and multiple clinical workflows. We find that good quality AI-based support of clinical decision-making improves diagnostic accuracy over that of either AI or physicians alone, and that the least experienced clinicians gain the most from AI-based support. We further find that AI-based multiclass probabilities outperformed content-based image retrieval (CBIR) representations of AI in the mobile technology environment, and AI-based support had utility in simulations of second opinions and of telemedicine triage. In addition to demonstrating the potential benefits associated with good quality AI in the hands of non-expert clinicians, we find that faulty AI can mislead the entire spectrum of clinicians, including experts. Lastly, we show that insights derived from AI class-activation maps can inform improvements in human diagnosis. Together, our approach and findings offer a framework for future studies across the spectrum of image-based diagnostics to improve human-computer collaboration in clinical practice. A systematic evaluation of the value of AI-based decision support in skin tumor diagnosis demonstrates the superiority of human-computer collaboration over each individual approach and supports the potential of automated approaches in diagnostic medicine.
|
|
| 7. |
|
|
| 8. |
- Cook, ER, et al.
(författare)
-
Old World megadroughts and pluvials during the Common Era
- 2015
-
Ingår i: Science Advances. - : American Association for the Advancement of Science (AAAS). - 2375-2548. ; 1:10
-
Tidskriftsartikel (refereegranskat)abstract
- Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other “Old World” climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the “Old World Drought Atlas” (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. TheOWDAmatches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability.
|
|
| 9. |
|
|
| 10. |
- Janda, Carsten Rudolf, et al.
(författare)
-
Wiretap-Channels under Constrained Active and Passive Attacks
- 2015
-
Ingår i: 2015 IEEE CONFERENCE ON COMMUNICATIONS AND NETWORK SECURITY (CNS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781467378765 ; , s. 16-21
-
Konferensbidrag (refereegranskat)abstract
- In this paper, the pessimistic multi letter common randomness assisted secrecy capacity for the Arbitrarily Varying Wiretap Channel (AVWC) under input and state constraints is derived.
|
|
