Medical image denoising using convolutional denoising autoencoders

Image denoising is an important pre-processing step in medical image analysis. Different algorithms have been proposed in past three decades with varying denoising performances. More recently, having outperformed all conventional methods, deep learning based models have shown a great promise. These methods are however limited for requirement of large training sample size and high computational costs. In this paper we show that using small sample size, denoising autoencoders constructed using convolutional layers can be used for efficient denoising of medical images. Heterogeneous images can be combined to boost sample size for increased denoising performance. Simplest of networks can reconstruct images with corruption levels so high that noise and signal are not differentiable to human eye.Comment: To appear: 6 pages, paper to be published at the Fourth Workshop on Data Mining in Biomedical Informatics and Healthcare at ICDM, 201

Recovering Loss to Followup Information Using Denoising Autoencoders

Loss to followup is a significant issue in healthcare and has serious consequences for a study's validity and cost. Methods available at present for recovering loss to followup information are restricted by their expressive capabilities and struggle to model highly non-linear relations and complex interactions. In this paper we propose a model based on overcomplete denoising autoencoders to recover loss to followup information. Designed to work with high volume data, results on various simulated and real life datasets show our model is appropriate under varying dataset and loss to followup conditions and outperforms the state-of-the-art methods by a wide margin ($\ge 20\%$ in some scenarios) while preserving the dataset utility for final analysis.Comment: Copyright IEEE 2017, IEEE International Conference on Big Data (Big Data

Competing risk survival analysis using SAS ® When, why and how

ABSTRACT Competing risk arise in time to event data when the event of interest cannot be observed because of a preceding event i.e. a competing event occurring before. An example can be of an event of interest being a specific cause of death where death from any other cause can be termed as a competing event, if focusing on relapse, death before relapse would constitute a competing event. It is well studied and pointed out that in presence of competing risks, the standard product limit methods yield biased results due to violation of their basic assumption. The effect of competing events on parameter estimation depends on their distribution and frequency. Fine and Gray's sub-distribution hazard model can be used in presence of competing events which is available in PROC PHREG with the release of version 9.4 of SAS ® software.

Comparison of One versus Two Fecal Immunochemical Tests in the Detection of Colorectal Neoplasia in a Population-Based Colorectal Cancer Screening Program

Objective. To determine the positive predictive value (PPV) of two versus one abnormal FIT in the detection of colorectal neoplasia in a Canadian population. Methods. Three communities enrolled in a colorectal cancer (CRC) screening pilot program from 01/2009 to 04/2013 using 2 FITs. Data collected included demographics, colonoscopy, pathology, and FIT results. Participants completed both FITs and had one positive FIT and colonoscopy. PPV of one versus two abnormal FITs was calculated using a weightedgeneralized score statistic. A two-sided 5% significance level was used. Results. 1576 of 17,031 average-risk participants, 50-75 years old, had a positive FIT. Colonoscopy revealed 58 (3.7%) cancers, 419 (31.6%) high-risk polyps, and 374 (23.7%) low-risk polyps as the most significant lesion. PPV of one versus two positive FITs for cancer, high-risk polyps, and any neoplasia were 1% versus 8%, 20% versus 40%, and 48% versus 67%, respectively ( value < 0.0001). When the first FIT was negative, the second positive FIT detected 7 CRCs and 98 high-risk polyps. Conclusions. PPV of two positive FITs is superior to one positive FIT for CRC and high-risk polyps. The added value of the second FIT was 12% of total CRCs and 23% of total high-risk polyps

Incorporating Item Frequency for Differentially Private Set Union

We study the problem of releasing the set union of users' items subject to differential privacy. Previous approaches consider only the set of items for each user as the input. We propose incorporating the item frequency, which is typically available in set union problems, to boost the utility of private mechanisms. However, using the global item frequency over all users would largely increase privacy loss. We propose to use the local item frequency of each user to approximate the global item frequency without incurring additional privacy loss. Local item frequency allows us to design greedy set union mechanisms that are differentially private, which is impossible for previous greedy proposals. Moreover, while all previous works have to use uniform sampling to limit the number of items each user would contribute to, our construction eliminates the sampling step completely and allows our mechanisms to consider all of the users' items. Finally, we propose to transfer the knowledge of the global item frequency from a public dataset into our mechanism, which further boosts utility even when the public and private datasets are from different domains. We evaluate the proposed methods on multiple real-life datasets

Current Attitudes toward Unfunded Cancer Therapies among Canadian Medical Oncologists

Background: Despite successes in the development of innovative anticancer therapies, the fiscal and capacity restraints of the Canadian public healthcare system result in challenges with drug access. A meaningful proportion of systemic therapies ultimately do not receive public funding despite supporting clinical evidence. In this study, we assessed Canadian medical oncologists’ current attitudes toward discussing publicly unfunded cancer treatments with patients and predictors of different practices. Methods: A web-based survey consisting of multiple choice and case-based scenarios was distributed to medical oncologists identified through the Royal College of Physicians and Surgeons of Canada directory. Results: A total of 116 responses were received. Almost all respondents reported discussing publicly unfunded treatments, including those who did so for Health Canada (HC) approved treatments (50%) and those who discussed off-label treatments (i.e., not HC approved) as guided by national guidelines (48%). Respondents in practice for over 15 years versus less than 5 years (OR 0.14, 95% CI 0.04–0.50, p = 0.002) and those who worked in a community practice versus comprehensive cancer center (OR 0.17, 95% CI 0.03–0.91, p = 0.04) were significantly less likely to discuss off-label treatment options with their patients. Almost half of respondents (47%) indicated that their institution did not permit the administration of unfunded treatments. Conclusions: There is variability in medical oncologists’ practices when it comes to discussing unfunded therapies. Given the limitations within Canada’s publicly funded healthcare system, physicians are faced with the challenge of navigating an increasingly complex balance between patient care and available resources. Engagement of relevant stakeholders and policy makers is crucial in the continued evaluation of Canada’s drug funding process

Current Attitudes toward Unfunded Cancer Therapies among Canadian Medical Oncologists

Background: Despite successes in the development of innovative anticancer therapies, the fiscal and capacity restraints of the Canadian public healthcare system result in challenges with drug access. A meaningful proportion of systemic therapies ultimately do not receive public funding despite supporting clinical evidence. In this study, we assessed Canadian medical oncologists’ current attitudes toward discussing publicly unfunded cancer treatments with patients and predictors of different practices. Methods: A web-based survey consisting of multiple choice and case-based scenarios was distributed to medical oncologists identified through the Royal College of Physicians and Surgeons of Canada directory. Results: A total of 116 responses were received. Almost all respondents reported discussing publicly unfunded treatments, including those who did so for Health Canada (HC) approved treatments (50%) and those who discussed off-label treatments (i.e., not HC approved) as guided by national guidelines (48%). Respondents in practice for over 15 years versus less than 5 years (OR 0.14, 95% CI 0.04–0.50, p = 0.002) and those who worked in a community practice versus comprehensive cancer center (OR 0.17, 95% CI 0.03–0.91, p = 0.04) were significantly less likely to discuss off-label treatment options with their patients. Almost half of respondents (47%) indicated that their institution did not permit the administration of unfunded treatments. Conclusions: There is variability in medical oncologists’ practices when it comes to discussing unfunded therapies. Given the limitations within Canada’s publicly funded healthcare system, physicians are faced with the challenge of navigating an increasingly complex balance between patient care and available resources. Engagement of relevant stakeholders and policy makers is crucial in the continued evaluation of Canada’s drug funding process

Sex Differences and Eating Disorder Risk Among Psychiatric Conditions, Compulsive Behaviors and Substance Use in a Screened Canadian National Sample

OBJECTIVE: This study examined sex differences and eating disorder risk among psychiatric conditions, compulsive behaviors (i.e., gambling, suicide thoughts and attempts) and substance use in a nationally representative sample. METHOD: Data from participants of the Canadian Community Health Survey Cycle 1.2 who completed the Eating Attitudes Test (n=5116) were analyzed. Sex differences were compared among psychiatric comorbidities according to eating disorder risk, binging, vomiting and dieting behavior. Poisson regression analysis provided prevalence ratios (PRs) of disordered eating adjusting for age, marital status, income, body mass index and recent distress. RESULTS: Pronounced sex differences were associated with eating disorder risk (PRs 4.89-11.04; all P values \u3c.0001). Findings of particular interest included significantly higher PRs for eating disorder risk in males associated with gambling (PR 5.07, P\u3c.0001) and for females associated with steroid and inhalant use as well as suicide thoughts and attempts (PRs 5.40-5.48, all P values \u3c.0001). DISCUSSION: The findings from this detailed exploration of sex differences and eating disorder risk among psychiatric conditions, compulsive behaviors and substance use suggest that problem gambling, the use of inhalants and steroids and suicidal ideation in relationship to eating disorder risk warrant further investigation