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We present a nonlinear data-driven Model Predictive Control (MPC) algorithm for deep brain stimulation (DBS) for the treatment of Parkinson's disease (PD). Although DBS is typically implemented in open-loop, closed-loop DBS (CLDBS) uses the…
Magnetic nanoparticles (MNPs) are the foundation of several new strategies for neural repair and neurological therapies. The fact that a remote force can act on MNPs at the cytoplasmic space constitutes the essence of many new…
Personalized medicine seeks to identify the causal effect of treatment for a particular patient as opposed to a clinical population at large. Most investigators estimate such personalized treatment effects by regressing the outcome of a…
Deep learning approaches, together with neuroimaging techniques, play an important role in psychiatric disorders classification. Previous studies on psychiatric disorders diagnosis mainly focus on using functional connectivity matrices of…
Deep brain stimulation (DBS) is an advanced surgical treatment for the symptoms of Parkinson's disease (PD), involving electrical stimulation of neurons within the basal ganglia region of the brain. DBS is traditionally delivered in an…
In both the fields of computer science and medicine there is very strong interest in developing personalized treatment policies for patients who have variable responses to treatments. In particular, I aim to find an optimal personalized…
In recent years, there has been a growing interest in the prediction of individualized treatment effects. While there is a rapidly growing literature on the development of such models, there is little literature on the evaluation of their…
Time series datasets are often composed of a variety of sequences from the same domain, but from different entities, such as individuals, products, or organizations. We are interested in how time series models can be specialized to…
A dynamic treatment regime is a sequence of treatment decision rules tailored to an individual's evolving status over time. In precision medicine, much focus has been placed on finding an optimal dynamic treatment regime which, if followed…
Beautiful theories of magnetic hysteresis based on random microscopic disorder have been developed over the past ten years. Our goal was to directly compare these theories with precise experiments. We first developed and then applied…
Closed-loop brain stimulation holds potential as personalized treatment for drug-resistant epilepsy (DRE) but still suffers from limitations that result in highly variable efficacy. First, stimulation is typically delivered upon detection…
Transformer-based models show their effectiveness across multiple domains and tasks. The self-attention allows to combine information from all sequence elements into context-aware representations. However, global and local information has…
In this paper, we propose a novel personalized decision support system that combines Theory of Mind (ToM) modeling and explainable Reinforcement Learning (XRL) to provide effective and interpretable interventions. Our method leverages DRL…
Posttraumatic stress disorder (PTSD) is a chronic and disabling neuropsychiatric disorder characterized by insufficient top-down modulation of the amygdala activity by the prefrontal cortex. Real-time fMRI neurofeedback (rtfMRI-nf) is an…
In the past decades mathematical optimization has found its way into radiation therapy and has made profound practice changing impact. Today, virtually all advanced treatment delivery methods, such as IMRT, VMAT, tomotherapy, LDR/HDR…
Background: Although it has been noticed that depressed patients show differences in processing emotions, the precise neural modulation mechanisms of positive and negative emotions remain elusive. FMRI is a cutting-edge medical imaging…
Single subject prediction of brain disorders from neuroimaging data has gained increasing attention in recent years. Yet, for some heterogeneous disorders such as major depression disorder (MDD) and autism spectrum disorder (ASD), the…
In this paper the research draws upon reminiscence therapy, which is used in treating dementia, as an applied theory to promote well being in people who experience low moods. The application proposed here aims to promote wellbeing for…
Reminiscence therapy is an inexpensive non-pharmacological therapy commonly used due to its therapeutic value for PwD, as it can be used to promote independence, positive moods and behavior, and improve their quality of life. Caregivers are…
Identifying patient subgroups with different treatment responses is an important task to inform medical recommendations, guidelines, and the design of future clinical trials. Existing approaches for treatment effect estimation primarily…