Parisa Rashidi
YOU?
Author Swipe
View article: Perioperative Artificial Intelligence Driven Integrated Modeling of Surgeries using Anesthetic, Physical and Cognitive Statuses for Predicting Hospital Outcomes
Perioperative Artificial Intelligence Driven Integrated Modeling of Surgeries using Anesthetic, Physical and Cognitive Statuses for Predicting Hospital Outcomes Open
The association between preoperative cognitive status and surgical outcomes is a critical yet scarcely explored area. We assessed how preoperative cognitive status, as measured by clock drawing tests, contributed to predicting length of ho…
View article: A large language model for delirium prediction in the intensive care unit using structured electronic health records
A large language model for delirium prediction in the intensive care unit using structured electronic health records Open
Delirium is an acute syndrome characterized by fluctuating attention, cognitive impairment, and severe disorganization of behavior, which has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection can …
View article: Reply: Underscoring the importance of surgical judgment
Reply: Underscoring the importance of surgical judgment Open
View article: Multi-hospital electronic decision support for drug-associated acute kidney injury (MEnD-AKI): Study protocol for a randomized clinical trial
Multi-hospital electronic decision support for drug-associated acute kidney injury (MEnD-AKI): Study protocol for a randomized clinical trial Open
ClinicalTrials.govNCT06264752 (v2).
View article: DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR
DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR Open
Delirium is an acute syndrome characterized by fluctuating attention, cognitive impairment, and severe disorganization ofbehavior, which has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection can e…
View article: Real-time prediction of intensive care unit patient acuity and therapy requirements using state-space modelling
Real-time prediction of intensive care unit patient acuity and therapy requirements using state-space modelling Open
View article: Selegiline’s Protective Role Against Elastase-Induced Oxidative Stress in A549 Cells via NRF2/Keap1 Pathway
Selegiline’s Protective Role Against Elastase-Induced Oxidative Stress in A549 Cells via NRF2/Keap1 Pathway Open
Background: Chronic obstructive pulmonary disease (COPD) is a global health concern characterized by oxidative stress and inflammation leading to lung tissue damage. Elastase contributes to the progression of COPD by increasing reactive ox…
View article: Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning.
Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning. Open
Our findings suggest that implementation of the model's policy has the potential to reduce postoperative AKI and improve other outcomes driven by intraoperative hypotension.
View article: Bridge2AI: Building A Cross-disciplinary Curriculum Towards AI-Enhanced Biomedical and Clinical Care
Bridge2AI: Building A Cross-disciplinary Curriculum Towards AI-Enhanced Biomedical and Clinical Care Open
Objective: As AI becomes increasingly central to healthcare, there is a pressing need for bioinformatics and biomedical training systems that are personalized and adaptable. Materials and Methods: The NIH Bridge2AI Training, Recruitment, a…
View article: Federated Learning for Predicting Major Postoperative Complications
Federated Learning for Predicting Major Postoperative Complications Open
Objective: To develop a robust model to accurately predict the risk of postoperative complications using clinical data from multiple institutions while ensuring data privacy. Background: Building accurate, artificial intelligence models to…
View article: XTSFormer: Cross-Temporal-Scale Transformer for Irregular-Time Event Prediction in Clinical Applications
XTSFormer: Cross-Temporal-Scale Transformer for Irregular-Time Event Prediction in Clinical Applications Open
Adverse clinical events related to unsafe care are among the top ten causes of death in the U.S. Accurate modeling and prediction of clinical events from electronic health records (EHRs) play a crucial role in patient safety enhancement. A…
View article: Human-Centered Development of an Explainable AI Framework for Real-Time Surgical Risk Surveillance
Human-Centered Development of an Explainable AI Framework for Real-Time Surgical Risk Surveillance Open
Background: Artificial Intelligence (AI) clinical decision support (CDS) systems have the potential to augment surgical risk assessments, but successful adoption depends on an understanding of end-user needs and current workflows. This stu…
View article: Validation of the MySurgeryRisk Algorithm for Predicting Complications and Death after Major Surgery: A Retrospective Multicenter Study Using OneFlorida Data Trust
Validation of the MySurgeryRisk Algorithm for Predicting Complications and Death after Major Surgery: A Retrospective Multicenter Study Using OneFlorida Data Trust Open
Despite advances in surgical techniques and care, postoperative complications are prevalent and effects up to 15% of the patients who underwent a major surgery. The objective of this study is to develop and validate models for predicting p…
View article: An Iterative, User-Centered Design of a Clinical Decision Support System for Critical Care Assessments: Co-Design Sessions with ICU Clinical Providers
An Iterative, User-Centered Design of a Clinical Decision Support System for Critical Care Assessments: Co-Design Sessions with ICU Clinical Providers Open
This study reports the findings of qualitative interview sessions conducted with ICU clinicians for the co-design of a system user interface of an artificial intelligence (AI)-driven clinical decision support (CDS) system. This system inte…
View article: Quantifying Circadian Desynchrony in ICU Patients and Its Association with Delirium
Quantifying Circadian Desynchrony in ICU Patients and Its Association with Delirium Open
Background: Circadian desynchrony characterized by the misalignment between an individual's internal biological rhythms and external environmental cues, significantly affects various physiological processes and health outcomes. Quantifying…
View article: Integrating Persian Lip Reading in Surena-V Humanoid Robot for Human-Robot Interaction
Integrating Persian Lip Reading in Surena-V Humanoid Robot for Human-Robot Interaction Open
Lip reading is vital for robots in social settings, improving their ability to understand human communication. This skill allows them to communicate more easily in crowded environments, especially in caregiving and customer service roles. …
View article: Building AI competence in the healthcare workforce with the AI for clinical care workshop: A Bridge2AI for clinical CHoRUS project
Building AI competence in the healthcare workforce with the AI for clinical care workshop: A Bridge2AI for clinical CHoRUS project Open
Background: The implementation of artificial intelligence (AI) tools into clinical spheres emphasizes the critical need for an AI-competent healthcare workforce that can interpret AI output and identify its limitations. Without comprehensi…
View article: Contextualising Responsible Innovation: A Framework for Governing Emerging Technologies
Contextualising Responsible Innovation: A Framework for Governing Emerging Technologies Open
View article: MANGO: Multimodal Acuity traNsformer for intelliGent ICU Outcomes
MANGO: Multimodal Acuity traNsformer for intelliGent ICU Outcomes Open
Estimation of patient acuity in the Intensive Care Unit (ICU) is vital to ensure timely and appropriate interventions. Advances in artificial intelligence (AI) technologies have significantly improved the accuracy of acuity predictions. Ho…
View article: Enhancing EHR Systems with data from wearables: An end-to-end Solution for monitoring post-Surgical Symptoms in older adults
Enhancing EHR Systems with data from wearables: An end-to-end Solution for monitoring post-Surgical Symptoms in older adults Open
Mobile health (mHealth) apps have gained popularity over the past decade for patient health monitoring, yet their potential for timely intervention is underutilized due to limited integration with electronic health records (EHR) systems. C…
View article: Peri-AIIMS: Perioperative Artificial Intelligence Driven Integrated Modeling of Surgeries using Anesthetic, Physical and Cognitive Statuses for Predicting Hospital Outcomes
Peri-AIIMS: Perioperative Artificial Intelligence Driven Integrated Modeling of Surgeries using Anesthetic, Physical and Cognitive Statuses for Predicting Hospital Outcomes Open
The association between preoperative cognitive status and surgical outcomes is a critical, yet scarcely explored area of research. Linking intraoperative data with postoperative outcomes is a promising and low-cost way of evaluating long-t…
View article: DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR
DeLLiriuM: A large language model for delirium prediction in the ICU using structured EHR Open
Delirium is an acute confusional state that has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection of this condition could lead to more timely interventions and improved health outcomes. While arti…
View article: Comparing the Efficacy of “Spray as You Go” Technique Versus Combined Airway Nerve Block and “Spray as You Go” as Topical Anesthesia During Flexible Bronchoscopy; a Double-Blinded Randomized Clinical Trial
Comparing the Efficacy of “Spray as You Go” Technique Versus Combined Airway Nerve Block and “Spray as You Go” as Topical Anesthesia During Flexible Bronchoscopy; a Double-Blinded Randomized Clinical Trial Open
Flexible bronchoscopy is employed to diagnose a range of respiratory disorders. Local airway anesthesia is mandatory to facilitate tracheal intubation. It is commonly done by injection of diluted lidocaine through working channel of bronch…
View article: Community-engaged artificial intelligence research: A scoping review
Community-engaged artificial intelligence research: A scoping review Open
The degree to which artificial intelligence healthcare research is informed by data and stakeholders from community settings has not been previously described. As communities are the principal location of healthcare delivery, engaging them…
View article: APRICOT-Mamba: Acuity Prediction in Intensive Care Unit (ICU): Development and Validation of a Stability, Transitions, and Life Sustaining Therapies Prediction Model
APRICOT-Mamba: Acuity Prediction in Intensive Care Unit (ICU): Development and Validation of a Stability, Transitions, and Life Sustaining Therapies Prediction Model Open
On average, more than 5 million patients are admitted to intensive care units (ICUs) in the US, with mortality rates ranging from 10 to 29%. The acuity state of patients in the ICU can quickly change from stable to unstable, sometimes lead…
View article: Developing a fair and interpretable representation of the clock drawing test for mitigating low education and racial bias
Developing a fair and interpretable representation of the clock drawing test for mitigating low education and racial bias Open
The clock drawing test (CDT) is a neuropsychological assessment tool to screen an individual's cognitive ability. In this study, we developed a Fair and Interpretable Representation of Clock drawing test (FaIRClocks) to evaluate and mitiga…
View article: Promoting AI Competencies for Medical Students: A Scoping Review on Frameworks, Programs, and Tools
Promoting AI Competencies for Medical Students: A Scoping Review on Frameworks, Programs, and Tools Open
As more clinical workflows continue to be augmented by artificial intelligence (AI), AI literacy among physicians will become a critical requirement for ensuring safe and ethical AI-enabled patient care. Despite the evolving importance of …
View article: Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning
Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning Open
View article: Transformers and large language models in healthcare: A review
Transformers and large language models in healthcare: A review Open
View article: Wearable sensors in patient acuity assessment in critical care
Wearable sensors in patient acuity assessment in critical care Open
Acuity assessments are vital for timely interventions and fair resource allocation in critical care settings. Conventional acuity scoring systems heavily depend on subjective patient assessments, leaving room for implicit bias and errors. …