The directors and members of the Intelligent Critical Care Center (IC3) have published over 1,500 articles in peer-reviewed, scholarly journals. These include journals such as Nature Reviews Nephrology, Scientific Reports, JAMA Internal Medicine, JAMA Network Open, The Lancet Digital Health, Medical Image Analysis, BMJ Health & Care Informatics, PLOS ONE, Kidney International, and Surgery.
Listed below are recent publications from some of the IC3 member labs. For more information on publications by specific IC3 members or labs, please refer to the IC3 Members page or the IC3 Labs page.
PRISMAP
IC3 co-director Azra Bihorac, associate directors of research Tyler Loftus and Tezcan Ozrazgat Baslanti, and assistant director of clinical AI Benjamin Shickel are all part of the Precision and Intelligent Systems in Medicine Research Partnership (PRISMAP) in the UF College of Medicine.
Correlating Deep Learning-Based Automated Reference Kidney Histomorphometry with Patient Demographics and Creatinine
CONCLUSIONS: Using deep learning, we automated precise measurements of kidney histomorphometric features. In the reference kidney tissue, several histomorphometric features demonstrated significant correlation to patient demographics, SCr, and eGFR. Deep…
Moving toward a contemporary classification of drug-induced kidney disease
Drug-induced kidney disease (DIKD) accounts for about one-fourth of all cases of acute kidney injury (AKI) in hospitalized patients, especially in critically ill setting. There is no standard definition or…
Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records
OBJECTIVE: This study aimed to develop and validate predictive models using electronic health records (EHR) data to determine whether hospitalized COVID-19-positive patients would be admitted to alternative medical care or…
Clinical courses of acute kidney injury in hospitalized patients: a multistate analysis
Persistence of acute kidney injury (AKI) or insufficient recovery of renal function was associated with reduced long-term survival and life quality. We quantified AKI trajectories and describe transitions through progression…
i-Heal Lab
IC3 co-director Parisa Rashidi leads the Intelligent Health Systems (i-Heal) Lab in the UF Herbert Wertheim College of Engineering.
FaIRClocks: Fair and Interpretable Representation of the Clock Drawing Test for mitigating classifier bias against lower educational groups
The clock drawing test (CDT) is a neuropsychological assessment tool to evaluate a patient’s cognitive ability. In this study, we developed a Fair and Interpretable Representation of Clock drawing tests…
Clinical courses of acute kidney injury in hospitalized patients: a multistate analysis
Persistence of acute kidney injury (AKI) or insufficient recovery of renal function was associated with reduced long-term survival and life quality. We quantified AKI trajectories and describe transitions through progression…
Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review
CONCLUSIONS: Shortcomings in current ML-CISs can be addressed by incorporating modular and interoperable data management, analytic platforms, secure interinstitutional data exchange, and application programming interfaces with adequate scalability to support…
Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup
Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the health of individuals in community, acute care and post-acute care settings. Although the recognition, prevention and…
CMI Lab
IC3 associate director of research Pinaki Sarder leads the Computational Microscopy Imaging (CMI) Lab in the UF College of Medicine.
Correlating Deep Learning-Based Automated Reference Kidney Histomorphometry with Patient Demographics and Creatinine
CONCLUSIONS: Using deep learning, we automated precise measurements of kidney histomorphometric features. In the reference kidney tissue, several histomorphometric features demonstrated significant correlation to patient demographics, SCr, and eGFR. Deep…
The Banff 2022 Kidney Meeting Work Plan: Data-driven Refinement of the Banff Classification for Renal Allografts
The XVI-th Banff Meeting for Allograft Pathology was held in Banff, Alberta, Canada, from 19th-23rd September 2022, as a joint meeting with the Canadian Society of Transplantation. In addition to…
Banff Digital Pathology Working Group: Image Bank, Artificial Intelligence Algorithm, and Challenge Trial Developments
The Banff Digital Pathology Working Group (DPWG) was established with the goal to establish a digital pathology repository; develop, validate, and share models for image analysis; and foster collaborations using…
Improving quantification of renal fibrosis using <em>Deep-DUET</em>
Accurate quantification of renal fibrosis has profound importance in the assessment of chronic kidney disease (CKD). Visual analysis of a biopsy stained with trichrome under the microscope by a pathologist…
SMILE Lab
IC3 associate director of education Ruogu Fang leads the Smart Medical Informatics Learning and Evaluation (SMILE) Lab in the UF Herbert Wertheim College of Engineering.
Ethnic disparity in diagnosing asymptomatic bacterial vaginosis using machine learning
While machine learning (ML) has shown great promise in medical diagnostics, a major challenge is that ML models do not always perform equally well among ethnic groups. This is alarming…
Machine-learning defined precision tDCS for improving cognitive function
CONCLUSIONS: The results of this study serve as a foundation for a custom dose optimization strategy towards precision medicine in tDCS to improve outcomes in cognitive decline remediation for older…
Emergence of Emotion Selectivity in A Deep Neural Network Trained to Recognize Visual Objects
Visual cortex plays an important role in representing the affective significance of visual input. The origin of these affect-specific visual representations is debated: they are innate to the visual system…