Patient-Specific Modeling and Model Predictive Control Approach to Personalized Optimal Anemia Management.

In the condition of anemia, kidneys produce less erythropoietin hormone to stimulate the bone marrow to make red blood cells (RBC) leading to a reduced hemoglobin (Hgb) level, also known as chronic kidney disease (CKD). External recombinant human erythropoietin (EPO) is administrated to maintain a healthy level of Hgb, i.e.

Convergence Analysis of Online Gradient Method for High-Order Neural Networks and Their Sparse Optimization.

In this article, we investigate the boundedness and convergence of the online gradient method with the smoothing group L regularization for the sigma-pi-sigma neural network (SPSNN). This enhances the sparseness of the network and improves its generalization ability. For the original group L regularization, the error function is nonconvex and nonsmooth, which can cause oscillation of the error function.

Control-Relevant Adaptive Personalized Modeling From Limited Clinical Data for Precise Warfarin Management.

Warfarin is a challenging drug to administer due to the narrow therapeutic index of the International Normalized Ratio (INR), the inter- and intra-variability of patients, limited clinical data, genetics, and the effects of other medications. To predict the optimal warfarin dosage in the presence of the aforementioned challenges, we present an adaptive individualized modeling framework based on model (In)validation and semi-blind robust system identification. The model (In)validation technique adapts the identified individualized patient model according to the change in the patient's status to ensure the model's suitability for prediction and controller design.

Precise Warfarin Management through Personalized Modeling and Control with Limited Clinical Data.

Warfarin belongs to a medication class called anticoagulants or blood thinners. It is used for the treatment to prevent blood clots from forming or growing larger. Patients with venous thrombosis, pulmonary embolism, or who have suffered a heart attack, have an irregular heartbeat, or prosthetic heart valves are prescribed with warfarin.

Adaptive Individualized Drug-Dose Response Modeling from a Limited Clinical Data: Case of Warfarin Management.

Administration of drugs requires sophisticated methods to determine the drug quantity for optimal results, and it has been a challenging task for the number of diseases. To solve these challenges, in this paper, we present the semi-blind robust model identification technique to find individualized patient models using the minimum number of clinically acquired patient-specific data to determine optimal drug dosage. To ensure the usability of these models for dosage predictability and controller design, the model (In)validation technique is also investigated.