Leveraging Computer Vision in the Intensive Care Unit (ICU) for Examining Visitation and Mobility
Fuente:
arXiv
Saved in:
| Main Authors: | Siegel, Scott, Zhang, Jiaqing, Bandyopadhyay, Sabyasachi, Nerella, Subhash, Silva, Brandon, Baslanti, Tezcan, Bihorac, Azra, Rashidi, Parisa |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
AI-Enhanced Intensive Care Unit: Revolutionizing Patient Care with Pervasive Sensing
by: Nerella, Subhash, et al.
Published: (2023)
by: Nerella, Subhash, et al.
Published: (2023)
Detecting Visual Cues in the Intensive Care Unit and Association with Patient Clinical Status
by: Nerella, Subhash, et al.
Published: (2023)
by: Nerella, Subhash, et al.
Published: (2023)
APRICOT-Mamba: Acuity Prediction in Intensive Care Unit (ICU): Development and Validation of a Stability, Transitions, and Life-Sustaining Therapies Prediction Model
by: Contreras, Miguel, et al.
Published: (2023)
by: Contreras, Miguel, et al.
Published: (2023)
MANGO: Multimodal Acuity traNsformer for intelliGent ICU Outcomes
by: Zhang, Jiaqing, et al.
Published: (2024)
by: Zhang, Jiaqing, et al.
Published: (2024)
DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR
by: Contreras, Miguel, et al.
Published: (2024)
by: Contreras, Miguel, et al.
Published: (2024)
MELON: Multimodal Mixture-of-Experts with Spectral-Temporal Fusion for Long-Term Mobility Estimation in Critical Care
by: Zhang, Jiaqing, et al.
Published: (2025)
by: Zhang, Jiaqing, et al.
Published: (2025)
Transformers in Healthcare: A Survey
by: Nerella, Subhash, et al.
Published: (2023)
by: Nerella, Subhash, et al.
Published: (2023)
MANDARIN: Mixture-of-Experts Framework for Dynamic Delirium and Coma Prediction in ICU Patients: Development and Validation of an Acute Brain Dysfunction Prediction Model
by: Contreras, Miguel, et al.
Published: (2025)
by: Contreras, Miguel, et al.
Published: (2025)
Quantifying Circadian Desynchrony in ICU Patients and Its Association with Delirium
by: Ren, Yuanfang, et al.
Published: (2025)
by: Ren, Yuanfang, et al.
Published: (2025)
A multi-cohort study on prediction of acute brain dysfunction states using selective state space models
by: Silva, Brandon, et al.
Published: (2024)
by: Silva, Brandon, et al.
Published: (2024)
Epidemiology, Trajectories and Outcomes of Acute Kidney Injury Among Hospitalized Patients: A Retrospective Multicenter Large Cohort Study
by: Adiyeke, Esra, et al.
Published: (2024)
by: Adiyeke, Esra, et al.
Published: (2024)
Validation of the MySurgeryRisk Algorithm for Predicting Complications and Death after Major Surgery: A Retrospective Multicenter Study Using OneFlorida Data Trust
by: Ren, Yuanfang, et al.
Published: (2025)
by: Ren, Yuanfang, et al.
Published: (2025)
Federated Learning with Multi-Partner OneFlorida+ Consortium Data for Predicting Major Postoperative Complications
by: Ren, Yuanfang, et al.
Published: (2026)
by: Ren, Yuanfang, et al.
Published: (2026)
An Iterative, User-Centered Design of a Clinical Decision Support System for Critical Care Assessments: Co-Design Sessions with ICU Clinical Providers
by: Davidson, Andrea E., et al.
Published: (2025)
by: Davidson, Andrea E., et al.
Published: (2025)
Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring
by: Zhang, Jiaqing, et al.
Published: (2026)
by: Zhang, Jiaqing, et al.
Published: (2026)
Federated learning model for predicting major postoperative complications
by: Park, Yonggi, et al.
Published: (2024)
by: Park, Yonggi, et al.
Published: (2024)
Human-Centered Development of an Explainable AI Framework for Real-Time Surgical Risk Surveillance
by: Davidson, Andrea E, et al.
Published: (2025)
by: Davidson, Andrea E, et al.
Published: (2025)
Transparent AI: Developing an Explainable Interface for Predicting Postoperative Complications
by: Ren, Yuanfang, et al.
Published: (2024)
by: Ren, Yuanfang, et al.
Published: (2024)
Temporal Cross-Attention for Dynamic Embedding and Tokenization of Multimodal Electronic Health Records
by: Ma, Yingbo, et al.
Published: (2024)
by: Ma, Yingbo, et al.
Published: (2024)
Peri-AIIMS: Perioperative Artificial Intelligence Driven Integrated Modeling of Surgeries using Anesthetic, Physical and Cognitive Statuses for Predicting Hospital Outcomes
by: Bandyopadhyay, Sabyasachi, et al.
Published: (2024)
by: Bandyopadhyay, Sabyasachi, et al.
Published: (2024)
Global Contrastive Training for Multimodal Electronic Health Records with Language Supervision
by: Ma, Yingbo, et al.
Published: (2024)
by: Ma, Yingbo, et al.
Published: (2024)
Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning
by: Adiyeke, Esra, et al.
Published: (2025)
by: Adiyeke, Esra, et al.
Published: (2025)
Promoting AI Competencies for Medical Students: A Scoping Review on Frameworks, Programs, and Tools
by: Ma, Yingbo, et al.
Published: (2024)
by: Ma, Yingbo, et al.
Published: (2024)
Unlocking Health Insights with SDoH Data: A Comprehensive Open-Access Database and SDoH-EHR Linkage Tool
by: Hu, Zhenhong, et al.
Published: (2025)
by: Hu, Zhenhong, et al.
Published: (2025)
Acute kidney injury prediction for non-critical care patients: a retrospective external and internal validation study
by: Adiyeke, Esra, et al.
Published: (2024)
by: Adiyeke, Esra, et al.
Published: (2024)
Between Compassion and Capacity: Intensive Care Units Nurses' Perceptions on Family‐Centred Visiting in China
by: Jiaying Xie, et al.
Published: (2026)
by: Jiaying Xie, et al.
Published: (2026)
The Impact of Open Visiting Policies on Patient, Family and Nursing Care: Nurses' Perceptions in Saudi Intensive Care Units
by: Rawia Ahmad Abdalla, et al.
Published: (2025)
by: Rawia Ahmad Abdalla, et al.
Published: (2025)
Nurse‐Led Early Mobility Protocols in the Intensive Care Unit
by: Ehizele Iyayi, et al.
Published: (2025)
by: Ehizele Iyayi, et al.
Published: (2025)
Challenges in Clinical Decision‐Making for Nurses in Neonatal Intensive Care Unit (NICU): A Qualitative Study
by: Fateme Mohammadi, et al.
Published: (2025)
by: Fateme Mohammadi, et al.
Published: (2025)
Perceived Barriers of Clinical Roles Towards Intensive Care Unit Mobility
by: Hassan Y. Aljohani, et al.
Published: (2024)
by: Hassan Y. Aljohani, et al.
Published: (2024)
An Algorithmic Approach for Causal Health Equity: A Look at Race Differentials in Intensive Care Unit (ICU) Outcomes
by: Plecko, Drago, et al.
Published: (2025)
by: Plecko, Drago, et al.
Published: (2025)
Drainage of Pleural Effusion in the Intensive Care Unit ( DOPE ‐ ICU ) Feasibility Trial—Protocol and Statistical Analysis Plan
by: Marie Schjødt Worm, et al.
Published: (2026)
by: Marie Schjødt Worm, et al.
Published: (2026)
PULSE-ICU: A Pretrained Unified Long-Sequence Encoder for Multi-task Prediction in Intensive Care Units
by: Jang, Sejeong, et al.
Published: (2025)
by: Jang, Sejeong, et al.
Published: (2025)
ICU Nurses' Perspectives on Artificial Intelligence in Adult Intensive Care Units: Knowledge, Attitudes and Job‐Security Concerns
by: Zahra Ahmed Sayed, et al.
Published: (2026)
by: Zahra Ahmed Sayed, et al.
Published: (2026)
Bridging the Digital Gap: A Thematic Qualitative Analysis of the Readiness of Intensive Care Unit (ICU) Nurses From an ICU in Indonesia to Adopt Electronic Nursing Records
by: Erna Dwi Wahyuni, et al.
Published: (2026)
by: Erna Dwi Wahyuni, et al.
Published: (2026)
Primary Nursing in Intensive Care Units
by: Lars Krüger, et al.
Published: (2026)
by: Lars Krüger, et al.
Published: (2026)
Clinical Profile and Outcome of Electrolyte Disturbances in Children Aged I Month tο 12 Years in Pediatric Intensive Care Unit of a Tertiary Care Hospital
by: Alpana Chanre, et al.
Published: (2025)
by: Alpana Chanre, et al.
Published: (2025)
Enhancing EHR Systems with data from wearables: An end-to-end Solution for monitoring post-Surgical Symptoms in older adults
by: Sun, Heng, et al.
Published: (2024)
by: Sun, Heng, et al.
Published: (2024)
The Healing Hermeneutics of Carnal Caring in Neonatal Intensive Care Units
by: Cas Wepener, et al.
Published: (2026)
by: Cas Wepener, et al.
Published: (2026)
Intensive Care Infection Score (ICIS) is an Early Marker for Infection in Time of Admission to Intensive Care Units
by: Filip Vrbacký, et al.
Published: (2025)
by: Filip Vrbacký, et al.
Published: (2025)
Similar Items
-
AI-Enhanced Intensive Care Unit: Revolutionizing Patient Care with Pervasive Sensing
by: Nerella, Subhash, et al.
Published: (2023) -
Detecting Visual Cues in the Intensive Care Unit and Association with Patient Clinical Status
by: Nerella, Subhash, et al.
Published: (2023) -
APRICOT-Mamba: Acuity Prediction in Intensive Care Unit (ICU): Development and Validation of a Stability, Transitions, and Life-Sustaining Therapies Prediction Model
by: Contreras, Miguel, et al.
Published: (2023) -
MANGO: Multimodal Acuity traNsformer for intelliGent ICU Outcomes
by: Zhang, Jiaqing, et al.
Published: (2024) -
DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR
by: Contreras, Miguel, et al.
Published: (2024)