CONTEXT The Texas Medication Algorithm Project is an evaluation of an algorithm-based disease management program for the treatment of the self-declared persistently and seriously mentally ill in the public mental health sector. OBJECTIVE To present clinical outcomes for patients with major depressive disorder (MDD) during 12-month algorithm-guided treatment (ALGO) compared with treatment as u...

In the Texas Medication Algorithm Project (TMAP), patients were given algorithm-guided treatment (ALGO) or treatment as usual (TAU). The ALGO intervention included a clinical coordinator to assist the physicians and administer a patient and family education program. The primary comparison in the schizophrenia module of TMAP was between patients seen in clinics in which ALGO was used (n = 165) a...

Covid-19 crisis has put the healthcare system under stress due to shortage of workers in hospitals, hour need is a highly flexible but dependable as well an sys- tem which can alert hospital authorities immediately through centralized relay about status patient if he/she becomes critical. Such may be built using Big Data enabled Wireless Sensor Networks, set up monitor patients inside shall mon...

In this paper we extend our previous work on model variety analysis of a signal processing algorithm with respect to the class of all input signals that may po tentially arise in a given signal understanding appli cation This analysis has two related objectives The rst objective is to partition the set of all possible sig nals in the application domain into two sets according to whether each si...

Previous algorithms for the construction of Bayesian belief network structures from data have been either highly dependent on con­ ditional independence (CI) tests, or have re­ quired an ordering on the nodes to be sup­ plied by the user. We present an algorithm that integrates these two approaches CI tests are used to generate an ordering on the nodes from the database which is then used to re...

The problem of expansion in powers is generalized into decomposition positive integers the sequence degrees different orders, con-ditions are determined, and algorithm for decomposi-tion constructed. based on two procedures: 1) achieve-ment a minimum residual at each step; 2) speeding decom-position through expanding local base by reducing in-dex, which ensures finiteness algorithm. has such ef...

In this paper, we consider the collaborative data publishingproblem for anonymizing horizontally partitioned data atmultiple data providers. We consider a new type of “in-sider attack” by colluding data providers who may use theirown data records (a subset of the overall data) in addition tothe external background knowledge to infer the data recordscontributed by other d...

This thesis addresses the problem of the unsupervised extraction of line networks (roads,rivers, etc.) from remotely sensed images. We use object processes, or marked point processes,as prior models. These models benefit from a stochastic framework (robustness w.r.t. noise,algorithms, etc.) while incorporating strong geometric constraints. Optimization is done viasimulated annea...