Imagen de Portada

Fast and Interpretable Mortality Risk Scores for Critical Care Patients

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhu, Chloe Qinyu, Tian, Muhang, Semenova, Lesia, Liu, Jiachang, Xu, Jack, Scarpa, Joseph, Rudin, Cynthia
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning Computers and Society
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
por: Liu, Jiachang, et al.
Publicado: (2024)

Amazing Things Come From Having Many Good Models
por: Rudin, Cynthia, et al.
Publicado: (2024)

OKRidge: Scalable Optimal k-Sparse Ridge Regression
por: Liu, Jiachang, et al.
Publicado: (2023)

Care Trajectories Are Linked to Mental Health and Mortality in Cancer Patients
por: Lindner, Simon D., et al.
Publicado: (2026)

ElliCE: Efficient and Provably Robust Algorithmic Recourse via the Rashomon Sets
por: Turbal, Bohdan, et al.
Publicado: (2026)

This EEG Looks Like These EEGs: Interpretable Interictal Epileptiform Discharge Detection With ProtoEEG-kNN
por: Tang, Dennis, et al.
Publicado: (2025)

Response to “Limitations in the Additive Risk Model Linking Visual Impairment and Poor Mobility to Mortality”
por: Atalie C. Thompson, et al.
Publicado: (2025)

Translating Machine Learning Interpretability into Clinical Insights for ICU Mortality Prediction
por: Liao, Ling, et al.
Publicado: (2025)

Models That Are Interpretable But Not Transparent
por: Zhong, Chudi, et al.
Publicado: (2025)

Association of Geriatric Emergency Department Care With Hospitalization and Mortality in Older Adults
por: Yuting Qian, et al.
Publicado: (2026)

The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning
por: Hsu, Ethan, et al.
Publicado: (2025)

Leo Breiman, the Rashomon Effect, and the Occam Dilemma
por: Rudin, Cynthia
Publicado: (2025)

Vehicle-group-based Crash Risk Prediction and Interpretation on Highways
por: Zhu, Tianheng, et al.
Publicado: (2024)

Limitations in the Additive Risk Model Linking Visual Impairment and Poor Mobility to Mortality
por: Hanadi Al Hamad, et al.
Publicado: (2025)

Enhancing Glycemic Risk Assessment in Long‐Term Care: Suggestions for Future Research
por: Zhen Xu, et al.
Publicado: (2025)

The Role of Risk Modeling in Advanced AI Risk Management
por: Touzet, Chloé, et al.
Publicado: (2025)

iScore: Visual Analytics for Interpreting How Language Models Automatically Score Summaries
por: Coscia, Adam, et al.
Publicado: (2024)

Risk, Data, Alignment: Making Credit Scoring Work in Kenya
por: Mwesigwa, Daniel, et al.
Publicado: (2026)

Reply to: Comment on “Tooth Loss and 12‐Year Mortality Risk in 8494 Older Adults From Ireland”
por: Lewis Winning, et al.
Publicado: (2025)

Co-design for Trustworthy AI: An Interpretable and Explainable Tool for Type 2 Diabetes Prediction Using Genomic Polygenic Risk Scores
por: Beuthan, Ralf, et al.
Publicado: (2026)

Editor's Note on Clin‐ STAR Corner: Practice‐Changing Advances in Diabetes Care
por: Joseph G. Ouslander
Publicado: (2025)

Considerations in Transition of Pediatric Neurology Patients to Adult Care
por: Asif Doja, et al.
Publicado: (2025)

A Methodology for Quantitative AI Risk Modeling
por: Murray, Malcolm, et al.
Publicado: (2025)

PAL: Designing Conversational Agents as Scalable, Cooperative Patient Simulators for Palliative-Care Training
por: Sehgal, Neil K. R., et al.
Publicado: (2025)

Semantic Risk Scoring of Aggregated Metrics: An AI-Driven Approach for Healthcare Data Governance
por: Ahmed, Mohammed Omer Shakeel
Publicado: (2026)

Same Patients, Different Health Care Systems—Revisited. Geriatric Care Models in the U.S., Canada, and Europe
por: Nathalie van der Velde, et al.
Publicado: (2026)

Is Power-Seeking AI an Existential Risk?
por: Carlsmith, Joseph
Publicado: (2022)

In Quest of an Extensible Multi-Level Harm Taxonomy for Adversarial AI: Heart of Security, Ethical Risk Scoring and Resilience Analytics
por: Khan, Javed I., et al.
Publicado: (2026)

Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data
por: Katta, Srikar, et al.
Publicado: (2023)

The CEKG: A Tool for Constructing Event Graphs in the Care Pathways of Multi-Morbid Patients
por: Aali, Milad Naeimaei, et al.
Publicado: (2024)

Second Volume of the Special Issue on: “Artificial Intelligence for Risk Analysis and the Risks of AI”
por: Vicki Bier, et al.
Publicado: (2026)

Association Between Frailty and Patients' Experience of Cancer Treatment and Care
por: Tomohiro F. Nishijima, et al.
Publicado: (2025)

Involvement of Patients With Cognitive Impairment and Care Partners in Advance Care Planning Decision‐Making: A Qualitative Study
por: Peiyuan Zhang, et al.
Publicado: (2026)

Interpretable Risk Mitigation in LLM Agent Systems
por: Chojnacki, Jan
Publicado: (2025)

Putnam's Critical and Explanatory Tendencies Interpreted from a Machine Learning Perspective
por: Soudin, Sheldon Z.
Publicado: (2025)

Risk-Adjusted Harm Scoring for Automated Red Teaming for LLMs in Financial Services
por: Dimino, Fabrizio, et al.
Publicado: (2026)

Meeting Patients Where They're At: Toward the Expansion of Chaplaincy Care into Online Spiritual Care Communities
por: Bezabih, Alemitu, et al.
Publicado: (2025)

Projecting Multimorbidity and Mortality under Demographic Change and Preventive Interventions
por: Ledebur, Katharina, et al.
Publicado: (2024)

A Learning Community to Advance Age‐Friendly Patient Priorities Care Nationally in the Program of All Inclusive Care of the Elderly
por: Claire E. Davenport, et al.
Publicado: (2026)

Unveiling Scoring Processes: Dissecting the Differences between LLMs and Human Graders in Automatic Scoring
por: Wu, Xuansheng, et al.
Publicado: (2024)