BACKGROUND Molar pregnancy represents a significant burden of disease on the spectrum of Gestational Trophoblastic Disease (GTD). The incidence appears to be quite high in South Asia. The objective of this study was to determine the frequency of GTD, and clinical presentation, management and outcome of patients with molar pregnancy. METHODS This retrospective, descriptive study was conducted ...

Quantification of cell-free DNA (cfDNA) in circulating blood derived from a transplanted organ is a powerful approach to monitoring post-transplant injury. Genome transplant dynamics (GTD) quantifies donor-derived cfDNA (dd-cfDNA) by taking advantage of single-nucleotide polymorphisms (SNPs) distributed across the genome to discriminate donor and recipient DNA molecules. In its current implemen...

Gestational trophoblastic disease (GTD) is a condition of uncertain etiology, choriocarcioma, or placental-site hydatidiform moles, invasive moles, choriocarcinoma, and placental-site trophoblastic tumors. It arises from the abnormal proliferation of trophoblastic tissue and spreads beyond the uterus hematogenously. The early diagnosis of GTD is important to ensure timely and successful managem...

Epithelioid trophoblastic tumor (ETT) is a very rare variant of gestational trophoblastic disease (GTD) which arises in reproductive age women with prior gestational history. Although abnormal vaginal bleeding is the most common symptom of ETT, there are no reported pathognomonic symptoms of ETT because of its rarity. ETT is similar to placental site trophoblastic tumor in terms of its slow gro...

We present a problem solving paradigm called generate, test and debug (GTD) that combines associational rules and causal models, producing a system with both the efficiency of rules and the breadth of problem solving power of causal models. The generator uses associational rules to generate plausible hypotheses; the tester uses causal models to test the hypotheses and produce a detailed charact...

In this paper, we show for the first time how gradient TD (GTD) reinforcement learning methods can be formally derived as true stochastic gradient algorithms, not with respect to their original objective functions as previously attempted, but rather using derived primal-dual saddle-point objective functions. We then conduct a saddle-point error analysis to obtain finite-sample bounds on their p...

Currently, the Genomic Threading Database (GTD) contains structural assignments for the proteins encoded within the genomes of nine eukaryotes and 101 prokaryotes. Structural annotations are carried out using a modified version of GenTHREADER, a reliable fold recognition method. The Gen THREADER annotation jobs are distributed across multiple clusters of processors using grid technology and the...

Choriocarcinoma is part of a rare spectrum of placental abnormalities known as gestational trophoblastic disease (GTD). It is the most invasive form of GTD, with a mortality rate approaching 100% if left untreated. It spreads predominantly hematogenously to multiple target sites, most commonly the lungs. Due to its hypervascular nature, it is often complicated by bleeding. We describe a case of...

In reinforcement learning (RL) , one of the key components is policy evaluation, which aims to estimate the value function (i.e., expected long-term accumulated reward) of a policy. With a good policy evaluation method, the RL algorithms will estimate the value function more accurately and find a better policy. When the state space is large or continuous Gradient-based Temporal Difference(GTD) ...