eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19 L Singhal, Y Garg, P Yang, A Tabaie, AI Wong, A Mohammed, L Chinthala, ... PloS one 16 (9), e0257056, 2021 | 35 | 2021 |
Temporal differential expression of physiomarkers predicts sepsis in critically ill adults A Mohammed, F Van Wyk, LK Chinthala, A Khojandi, RL Davis, ... Shock 56 (1), 58-64, 2021 | 34 | 2021 |
HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study Z Liu, A Khojandi, A Mohammed, X Li, LK Chinthala, RL Davis, ... Computers in biology and medicine 131, 104255, 2021 | 11 | 2021 |
Predicting Parkinson’s disease and its pathology via simple clinical variables I Karabayir, L Butler, SM Goldman, R Kamaleswaran, F Gunturkun, ... Journal of Parkinson's Disease 12 (1), 341-351, 2022 | 8 | 2022 |
Analyzing relationships between economic and neighborhood-related social determinants of health and intensive care unit length of stay for critically ill children with medical … H Hamilton, AN West, N Ammar, L Chinthala, F Gunturkun, T Jones, ... Frontiers in Public Health 10, 789999, 2022 | 6 | 2022 |
Traveling for pancreatic cancer care is worth the trip MA Alvarez, K Anderson, JL Deneve, PV Dickson, D Yakoub, MD Fleming, ... The American Surgeon 87 (4), 549-556, 2021 | 5 | 2021 |
FEASIBILITY OF REMOTE MONITORING FOR FATAL CORONARY HEART DISEASE FROM SINGLE LEAD ECG L Butler, T Celik, I Karabayir, L Chinthala, MS Tootooni, DD McManus, ... Cardiovascular Digital Health Journal 4 (5), S1, 2023 | 3 | 2023 |
Machine learning predicts early onset of fever from continuous physiological data of critically ill patients A Singh, A Mohammed, L Chinthala, R Kamaleswaran arXiv preprint arXiv:2009.07103, 2020 | 3 | 2020 |
Externally validated deep learning model to identify prodromal Parkinson’s disease from electrocardiogram I Karabayir, F Gunturkun, L Butler, SM Goldman, R Kamaleswaran, ... Scientific Reports 13 (1), 12290, 2023 | 2 | 2023 |
Augmenting Machine Learning with Statistical Testing: A Novel Method for Early Sepsis Prediction Z Liu, A Khojandi, A Mohammed, X Li, LK Chinthala, RL Davis, ... preprint, 2020 | 2 | 2020 |
A real world evidence for the performance of an ecg-ai based heart failure risk predictor O Akbilgic, I Karabayir, L Butler, F Güntürkün, L Chinthala, JL Jefferies, ... Journal of the American College of Cardiology 81 (8_Supplement), 727-727, 2023 | 1 | 2023 |
Time-Dependent ECG-AI Prediction of Fatal Coronary Heart Disease L Butler, A Ivanov, T Celik, I Karabayir, L Chinthala, MS Tootooni, ... medRxiv, 2023.10. 11.23296910, 2023 | 1 | 2023 |
Features derived from blood pressure and intracranial pressure predict elevated intracranial pressure events in critically ill children K Ackerman, A Mohammed, L Chinthala, RL Davis, R Kamaleswaran, ... Scientific Reports 12 (1), 21473, 2022 | 1 | 2022 |
Externally validated AI model to identify prodromal Parkinson’s disease from ECG O Akbilgic, I KARABAYIR, F Gunturkun, S Goldman, R Kamaleswaran, ... | 1 | 2022 |
Human-Computer Interface of Low-Cost Abductor Digiti Minimi Monitoring System Using sEMG S Vivekanandan, LC Kumar, M Devanand, DS Emmanuel International Journal of Pharma Medicine and Biological Sciences 4 (2), 128, 2015 | 1 | 2015 |
Feasibility of Remote Monitoring for Fatal Coronary Heart Disease using Apple Watch ECGs L Butler, A Ivanov, T Celik, I Karabayir, L Chinthala, MM Hudson, KK Ness, ... Cardiovascular Digital Health Journal, 2024 | | 2024 |
ECG-AI FOR BLOOD PRESSURE ESTIMATION I Karabayir, R Davis, L Chinthala, L Butler, T Celik, U Kilic, O Akbilgic Journal of the American College of Cardiology 83 (13_Supplement), 2646-2646, 2024 | | 2024 |
Single Lead Wearable ECG Simulation Augmented with AI for Heart Failure Identification I Karabayir, R Davis, L Chinthala, L Butler, T Celik, U Kilic, O Akbilgic Journal of the American College of Cardiology 83 (13_Supplement), 2393-2393, 2024 | | 2024 |
GSDMB/ORMDL3 Rare/Common Variants Are Associated with Inhaled Corticosteroid Response among Children with Asthma K Voorhies, A Mohammed, L Chinthala, SW Kong, IH Lee, AT Kho, ... Genes 15 (4), 420, 2024 | | 2024 |
Development and Validation of an Electrocardiographic Artificial Intelligence Model for Detection of Peripartum Cardiomyopathy I Karabayir, G Wilkie, T Celik, L Butler, L Chinthala, A Ivanov, TAM Simas, ... American Journal of Obstetrics & Gynecology MFM, 101337, 2024 | | 2024 |