| Nome |
# |
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La Scienza Dei Dati, file e39773b6-fc34-35a3-e053-3a05fe0aac26
|
4.696
|
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Interpretable heartbeat classification using local model-agnostic explanations on ECGs, file e39773b7-e53d-35a3-e053-3a05fe0aac26
|
739
|
|
La Scienza Dei Dati, file e39773b6-d5d7-35a3-e053-3a05fe0aac26
|
668
|
|
The need to move away from agential-AI: Empirical investigations, useful concepts and open issues, file e39773b8-0d4f-35a3-e053-3a05fe0aac26
|
594
|
|
The importance of being external. methodological insights for the external validation of machine learning models in medicine, file e39773b8-0d51-35a3-e053-3a05fe0aac26
|
509
|
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The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studies, file e39773b7-e7a2-35a3-e053-3a05fe0aac26
|
398
|
|
The three-way-in and three-way-out framework to treat and exploit ambiguity in data, file e39773b6-a2cb-35a3-e053-3a05fe0aac26
|
301
|
|
Rams, hounds and white boxes: Investigating human–AI collaboration protocols in medical diagnosis, file 4876cb11-48f3-4f97-ba12-13532c5b43b7
|
296
|
|
Digitizing the informed consent: The challenges to design for practices, file e39773b5-acb1-35a3-e053-3a05fe0aac26
|
269
|
|
An Adaptive Middleware to Support Context-Aware Knowledge Sharing, file e39773b1-367f-35a3-e053-3a05fe0aac26
|
252
|
|
Bridging the "last mile" gap between AI implementation and operation: "data awareness" that matters, file e39773b6-a291-35a3-e053-3a05fe0aac26
|
213
|
|
Prediction of ICU admission for COVID-19 patients: A machine learning approach based on complete blood count data, file e39773b8-26b8-35a3-e053-3a05fe0aac26
|
211
|
|
Three-way decision and conformal prediction: Isomorphisms, differences and theoretical properties of cautious learning approaches, file e39773b8-30ce-35a3-e053-3a05fe0aac26
|
205
|
|
Machine learning in orthopedics: A literature review, file e39773b7-9ab6-35a3-e053-3a05fe0aac26
|
188
|
|
The Revival of the Notes Field: Leveraging the Unstructured Content in Electronic Health Records, file e39773b5-ceac-35a3-e053-3a05fe0aac26
|
139
|
|
Data work in healthcare: An Introduction, file e39773b7-9740-35a3-e053-3a05fe0aac26
|
105
|
|
To Err is (only) Human. Reflections on How to Move from Accuracy to Trust for Medical AI, file 75d43f7f-8d7d-498e-bcc2-d7f530ece53d
|
97
|
|
IGV short scale to assess implicit value of visualizations through explicit interaction, file e39773b7-3cd1-35a3-e053-3a05fe0aac26
|
96
|
|
Studying human-AI collaboration protocols: the case of the Kasparov's law in radiological double reading, file e39773b7-4b71-35a3-e053-3a05fe0aac26
|
87
|
|
The elephant in the machine: Proposing a new metric of data reliability and its application to a medical case to assess classification reliability, file e39773b7-2cee-35a3-e053-3a05fe0aac26
|
85
|
|
Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings, file e39773b6-829e-35a3-e053-3a05fe0aac26
|
68
|
|
As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI, file e39773b7-3b00-35a3-e053-3a05fe0aac26
|
68
|
|
Open, Multiple, Adjunct. Decision Support at the Time of Relational AI, file b0ca376b-2d68-4801-81e0-7eb9ddc7c217
|
47
|
|
CASMAS-WOAD to Achieve Integrated Care and Coordination among Heterogeneous Care Communities, file e39773b1-8210-35a3-e053-3a05fe0aac26
|
38
|
|
Unity is intelligence: a collective intelligence experiment on ecg reading to improve diagnostic performance in cardiology, file e39773b7-e7a0-35a3-e053-3a05fe0aac26
|
38
|
|
Machine Learning for Health: Algorithm Auditing & Quality Control, file ace30e6b-c3ee-4f73-89dc-585740782a6f
|
28
|
|
Open, Multiple, Adjunct. Decision Support at the Time of Relational AI, file 815b91a6-3fd7-4f7a-a874-f7a15ec6b090
|
25
|
|
Everything is varied: The surprising impact of instantial variation on ML reliability, file 88acd097-b314-405c-870b-75367e74c216
|
25
|
|
Has the flood entered the basement? A systematic literature review about machine learning in laboratory medicine, file 05205c33-8c71-43a3-9c7f-45a0115f3bc0
|
24
|
|
Towards a Rigorous Calibration Assessment Framework: Advancements in Metrics, Methods, and Use, file 3998da14-0e54-49d1-8a14-4af87f9226c7
|
18
|
|
Painting the Black Box White: Experimental Findings from Applying XAI to an ECG Reading Setting, file c2a78682-c078-4ecf-bf90-8d3eeadbe4fd
|
18
|
|
Evaluation of uncertainty quantification methods in multi-label classification: A case study with automatic diagnosis of electrocardiogram, file 2feb27ec-3218-4793-980a-93816a302bed
|
17
|
|
Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition, file 77cd0d0b-afdb-45ce-91d3-7681fae2f300
|
13
|
|
Assessment of Fast-Track Pathway in Hip and Knee Replacement Surgery by Propensity Score Matching on Patient-Reported Outcomes, file 7207532c-e811-4a96-a323-bdbc5ea233bc
|
10
|
|
The Tower of Babel in Explainable Artificial Intelligence (XAI), file 140ea307-5d3c-4fdb-80fd-5f2b1ecbbac8
|
8
|
|
Applications of deep learning in dentistry, file 5c0f64bd-b83f-4805-af0e-a01cc49c7824
|
7
|
|
Evidence-based XAI: An empirical approach to design more effective and explainable decision support systems, file 37e3503f-65eb-4060-901c-94541709c2cc
|
6
|
|
Controllable AI - An Alternative to Trustworthiness in Complex AI Systems?, file 6a168c11-ccf3-45f6-9186-66c3e89cc590
|
6
|
|
Never tell me the odds: Investigating pro-hoc explanations in medical decision making, file 8debd793-fecf-42e6-8d2b-13bb9f64e143
|
6
|
|
Never tell me the odds: Investigating pro-hoc explanations in medical decision making, file 12f5eb29-bc5f-4766-9f9e-121216927da9
|
5
|
|
A parsimonious machine learning approach to detect inappropriate treatments in spine surgery on the basis of patient-reported outcomes, file 934db788-40c3-4b67-adb0-9ca728d620ce
|
5
|
|
The Impact of Gender and Personality in Human-AI Teaming: The Case of Collaborative Question Answering, file 344c186f-94a8-4ab1-8788-63b4460cbe38
|
4
|
|
User-driven prioritization of features for a prospective InterPersonal Health Record: Perceptions from the Italian context, file e39773b8-5004-35a3-e053-3a05fe0aac26
|
3
|
|
Demo: Decision Support System Quality Assessment Tool, file 0064f9b4-b8b6-4071-ab87-f4fd60f79ba8
|
2
|
|
AI Shall Have No Dominion: on How to Measure Technology Dominance in AI-supported Human decision-making, file 23d47be9-4972-462d-970d-f52db67aa95a
|
2
|
|
Back to the Feature: A Neural-Symbolic Perspective on Explainable AI, file 72c22da0-d43e-4df0-a363-7135f9da3e16
|
2
|
|
Weighted Utility: A Utility Metric Based on the Case-Wise Raters’ Perceptions, file 77b808b4-a68e-49ee-a623-4416b246f30b
|
2
|
|
Toward a Perspectivist Turn in Ground Truthing for Predictive Computing, file 8fb56ed5-589f-4c4c-b3b7-4be56d8af857
|
2
|
|
Ensemble Predictors: Possibilistic Combination of Conformal Predictors for Multivariate Time Series Classification, file a41a1b9d-9323-435d-96a7-d4a45e202fb0
|
2
|
|
Let Me Think! Investigating the Effect of Explanations Feeding Doubts About the AI Advice, file cd049d22-c634-4af3-b47f-b6bd3253b1b9
|
2
|
|
Knowledge artifacts within Knowing communities to foster Collective Knowledge, file e39773b3-6f0e-35a3-e053-3a05fe0aac26
|
2
|
|
Color Shadows 2: Assessing the Impact of XAI on Diagnostic Decision-Making, file fbe166e6-c1b6-4121-bd72-3c0f73c7f425
|
2
|
|
On a QUESt for a web-based tool promoting knowledge-sharing in medical communities, file e39773b3-7361-35a3-e053-3a05fe0aac26
|
1
|
|
Management of knee injuries: consensus-based indications from a large community of orthopaedic surgeons, file e39773b3-7365-35a3-e053-3a05fe0aac26
|
1
|
|
Tendon-Derived Stem Cells for Rotator Cuff Repair, file e39773b3-74a8-35a3-e053-3a05fe0aac26
|
1
|
|
The proof of the pudding: in praise of a culture of real-world validation for medical artificial intelligence, file e39773b6-42a6-35a3-e053-3a05fe0aac26
|
1
|
| Totale |
10.657 |
