A Medical Literature Search System for Identifying Effective Treatments in Precision Medicine

The Precision Medicine Initiative states that treatments for a patient should take into account not only the patient’s disease, but his/her specific genetic variation as well. The vast biomedical literature holds the potential for physicians to identify effective treatment options for a cancer patient. However, the complexity and ambiguity of medical terms can result in vocabulary mismatch between the physician’s query and the literature. The physician’s search intent (finding treatments instead of other types of studies) is difficult to explicitly formulate in a query. Therefore, simple ad hoc retrieval approach will suffer from low recall and precision.In this paper, we propose a new retrieval system that helps physicians identify effective treatments in precision medicine. Given a cancer patient with a specific disease, genetic variation, and demographic information, the system aims to identify biomedical publications that report effective treatments. We approach this goal from two directions. First, we expand the original disease and gene terms using biomedical knowledge bases to improve recall of the initial retrieval. We then improve precision by promoting treatment-related publications to the top using a machine learning reranker trained on 2017 Text Retrieval Conference Precision Medicine (PM) track corpus. Batch evaluation results on 2018 PM track corpus show that the proposed approach effectively improves both recall and precision, achieving performance comparable to the top entries on the leaderboard of 2018 PM track.Master of Science in Information Scienc

Protocol for a randomized controlled trial examining multilevel prediction of response to behavioral activation and exposure-based therapy for generalized anxiety disorder.

BACKGROUND:Only 40-60% of patients with generalized anxiety disorder experience long-lasting improvement with gold standard psychosocial interventions. Identifying neurobehavioral factors that predict treatment success might provide specific targets for more individualized interventions, fostering more optimal outcomes and bringing us closer to the goal of "personalized medicine." Research suggests that reward and threat processing (approach/avoidance behavior) and cognitive control may be important for understanding anxiety and comorbid depressive disorders and may have relevance to treatment outcomes. This study was designed to determine whether approach-avoidance behaviors and associated neural responses moderate treatment response to exposure-based versus behavioral activation therapy for generalized anxiety disorder. METHODS/DESIGN:We are conducting a randomized controlled trial involving two 10-week group-based interventions: exposure-based therapy or behavioral activation therapy. These interventions focus on specific and unique aspects of threat and reward processing, respectively. Prior to and after treatment, participants are interviewed and undergo behavioral, biomarker, and neuroimaging assessments, with a focus on approach and avoidance processing and decision-making. Primary analyses will use mixed models to examine whether hypothesized approach, avoidance, and conflict arbitration behaviors and associated neural responses at baseline moderate symptom change with treatment, as assessed using the Generalized Anxiety Disorder-7 item scale. Exploratory analyses will examine additional potential treatment moderators and use data reduction and machine learning methods. DISCUSSION:This protocol provides a framework for how studies may be designed to move the field toward neuroscience-informed and personalized psychosocial treatments. The results of this trial will have implications for approach-avoidance processing in generalized anxiety disorder, relationships between levels of analysis (i.e., behavioral, neural), and predictors of behavioral therapy outcome. TRIAL REGISTRATION:The study was retrospectively registered within 21 days of first participant enrollment in accordance with FDAAA 801 with ClinicalTrials.gov, NCT02807480. Registered on June 21, 2016, before results

Treatment for depression following mild traumatic brain injury in adults: A meta-analysis

Primary objective: Development of depression after TBI is linked to poorer outcomes. The aim of this manuscript is to review evidence for the effectiveness of current treatments. Research design: Two meta-analyses were undertaken to examine the effectiveness of both pharmacological and non-pharmacological interventions for depression after mild TBI Method and procedures: PubMed, Medline, PsychInfo, Web of Science and Digital Dissertations were searched and 13 studies located. Meta Analyst Beta 3.13 was used to conduct analyses of pre- vs post-effects then to examine treatment group vs control group effects. Main outcomes and results: Studies using a pre–post design produced an overall effect size of 1.89 (95% CI = 1.20–2.58, p < 0.001), suggesting that treatments were effective; however, the overall effect for controlled trials was 0.46 (95% CI = −0.44–1.36, p < 0.001), which favoured the control rather than treatment groups. Conclusions: This study highlights the need for additional large well-controlled trials of effective treatments for depression post-TBI

Clinical applications of personalized medicine: a new paradigm and challenge

The personalized medicine is an emergent and rapidly developing method of clinical practice that uses new technologies to provide decisions in regard to the prediction, prevention, diagnosis and treatment of disease. The continue evolution of technology and the developments in molecular diagnostics and genomic analysis increased the possibility of an even more understanding and interpretation of the human genome and exome, allowing a "personalized" approach to clinical care, so that the concepts of "Systems Medicine" and "System Biology" are increasingly actual. The purpose of this study is to evaluate the personalized medicine about its indications and benefits, actual clinical applications and future perspectives as well as its issues and health care implications. It was made a careful review of the scientific literature on this field that highlighted the applicability and usefulness of this new medical approach as well as the fact that personalized medicine strategy is even more increasing in numerous fields of applications

NHMRC information paper: evidence on the effectiveness of homeopathy for treating health conditions

This paper provides a summary of evidence from research on the effectiveness of homeopathy in treating health conditions in humans. Findings There was no reliable evidence from research in humans that homeopathy was effective for treating the range of health conditions considered: no good-quality, well-designed studies with enough participants for a meaningful result reported either that homeopathy caused greater health improvements than placebo, or caused health improvements equal to those of another treatment. For some health conditions, studies reported that homeopathy was not more effective than placebo. For other health conditions, there were poor-quality studies that reported homeopathy was more effective than placebo, or as effective as another treatment. However, based on their limitations, those studies were not reliable for making conclusions about whether homeopathy was effective. For the remaining health conditions it was not possible to make any conclusion about whether homeopathy was effective or not, because there was not enough evidence. Conclusions Based on the assessment of the evidence of effectiveness of homeopathy, NHMRC concludes that there are no health conditions for which there is reliable evidence that homeopathy is effective. Homeopathy should not be used to treat health conditions that are chronic, serious, or could become serious. People who choose homeopathy may put their health at risk if they reject or delay treatments for which there is good evidence for safety and effectiveness. People who are considering whether to use homeopathy should first get advice from a registered health practitioner. Those who use homeopathy should tell their health practitioner and should keep taking any prescribed treatments