| Narendra N Khanna, Mahesh A Maindarkar, Vijay Viswanathan, Anudeep Puvvula, Sudip Paul, Mrinalini Bhagawati, Puneet Ahluwalia, Zoltan Ruzsa, Aditya Sharma, Raghu Kolluri, Padukone R Krishnan, Inder M Singh, John R Laird, Mostafa Fatemi, Azra Alizad, Surinder K Dhanjil, Luca Saba, Antonella Balestrieri, Gavino Faa, Kosmas I Paraskevas, Durga Prasanna Misra, Vikas Agarwal, Aman Sharma, Jagjit S Teji, Mustafa Al-Maini, Andrew Nicolaides, Vijay Rathore, Subbaram Naidu, Kiera Liblik, Amer M Johri, Monika Turk, David W Sobel, Martin Miner, Klaudija Viskovic, George Tsoulfas, Athanasios D Protogerou, Sophie Mavrogeni, George D Kitas, Mostafa M Fouda, Mannudeep K Kalra, Jasjit S Sur. Cardiovascular/Stroke Risk Stratification in Diabetic Foot Infection Patients Using Deep Learning-Based Artificial Intelligence: An Investigative Study. Journal of clinical medicine. vol 11. issue 22. 2022-11-26. PMID:36431321. |
since surrogate biomarkers for cad, such as carotid artery disease, can be used for monitoring cvd, we can thus use a dl-based model, namely, long short-term memory (lstm) and recurrent neural networks (rnn) for cvd/stroke risk prediction in dfi patients, which combines covariates such as office and laboratory-based biomarkers, carotid ultrasound image phenotype (cusip) lesions, along with the dfi severity. |
2022-11-26 |
2023-08-14 |
Not clear |