Novel Approach to Cluster Patient-Generated Data Into Actionable Topics: Case Study of a Web-Based Breast Cancer Forum

Background: The increasing use of social media and mHealth apps has generated new opportunities for health care consumers to share information about their health and well-being. Information shared through social media contains not only medical information but also valuable information about how the survivors manage disease and recovery in the context of daily life. Objective: The objective of this study was to determine the feasibility of acquiring and modeling the topics of a major online breast cancer support forum. Breast cancer patient support forums were selected to discover the hidden, less obvious aspects of disease management and recovery. Methods: First, manual topic categorization was performed using qualitative content analysis (QCA) of each individual forum board. Second, we requested permission from the Breastcancer.org Community for a more in-depth analysis of the postings. Topic modeling was then performed using open source software Machine Learning Language Toolkit, followed by multiple linear regression (MLR) analysis to detect highly correlated topics among the different website forums. Results: QCA of the forums resulted in 20 categories of user discussion. The final topic model organized >4 million postings into 30 manageable topics. Using qualitative analysis of the topic models and statistical analysis, we grouped these 30 topics into 4 distinct clusters with similarity scores of ≥0.80; these clusters were labeled Symptoms & Diagnosis, Treatment, Financial, and Family & Friends. A clinician review confirmed the clinical significance of the topic clusters, allowing for future detection of actionable items within social media postings. To identify the most significant topics across individual forums, MLR demonstrated that 6 topics—based on the Akaike information criterion values ranging from −642.75 to −412.32—were statistically significant. Conclusions: The developed method provides an insight into the areas of interest and concern, including those not ascertainable in the clinic. Such topics included support from lay and professional caregivers and late side effects of therapy that consumers discuss in social media and may be of interest to clinicians. The developed methods and results indicate the potential of social media to inform the clinical workflow with regards to the impact of recovery on daily life. [JMIR Med Inform 2018;6(4):e45

What Do They Mean by "Health Informatics"? Health Informations Posts Compared to Program Standards

There is a lack of alignment between and within the competencies and skills required by health informatics (HI) related jobs and those present in academic curriculum frameworks. This study uses computational topic modeling for gap analysis of career needs vs. curriculum objectives. The seven AMIA-CAHIIM-accepted core knowledge domains were used to categorize a corpus of HI-related job postings (N = 475) from a major United States-based job posting website. Computational modeling-generated topics were created and then compared and matched to the seven core knowledge domains. The HI-defining core domain, representing the intersection of health, technology and social/behavioral sciences matched only 45.9% of job posting content. Therefore, the authors suggest that bidirectional communication between academia and industry is needed in order to better align educational objectives to the demands of the job market

A Panel of Cytochrome P450 BM3 Variants to Produce Drug Metabolites and Diversify Lead Compounds

Herein we demonstrate that a small panel of variants of cytochrome P450 BM3 from Bacillus megaterium covers the breadth of reactivity of human P450s by producing 12 of 13 mammalian metabolites for two marketed drugs, verapamil and astemizole, and one research compound. The most active enzymes support preparation of individual metabolites for preclinical bioactivity and toxicology evaluations. Underscoring their potential utility in drug lead diversification, engineered P450 BM3 variants also produce novel metabolites by catalyzing reactions at carbon centers beyond those targeted by animal and human P450s. Production of a specific metabolite can be improved by directed evolution of the enzyme catalyst. Some variants are more active on the more hydrophobic parent drug than on its metabolites, which limits production of multiply-hydroxylated species, a preference that appears to depend on the evolutionary history of the P450 variant

Stereoselective synthesis of hydroxylated 3-aminoazepanes using a multi-bond forming, three-step tandem process

A multi-bond forming, three-step tandem process involving a palladium(II)-catalysed Overman rearrangement and a ring closing metathesis reaction has been utilised for the efficient synthesis of a 2,3,6,7-tetrahydro-3-amidoazepine. Substrate directed epoxidation or dihydroxylation of this synthetic intermediate has allowed the diastereoselective synthesis of hydroxylated 3-aminoazepanes including the syn-diastereomer of the balanol core. Asymmetric synthesis of the 2,3,6,7-tetrahydro-3-amidoazepine motif was also achieved using a chiral palladium(II)-catalyst during the Overman rearrangement

NEURAL NETWORK BASED AGE CLASSIFICATION USING LINEAR WAVELET TRANSFORMS

The facial image analysis for classifying human age has a vital role in Image processing, Pattern recognition, Computer vision, Cognitive science and Forensic science. The various computational and mathematical models, for classifying facial age includes Principal Component Analysis (PCA) and Wavelet Transforms and Local Binary Pattern (LBP). A more sophisticated method is introduced to improve the performance of the system by decomposing the face image using 2-level linear wavelet transforms and classifying the human age group using Artificial Neural Network. This approach needs normalizing the facial image at first and then extracting the face features using linear wavelet transforms. The distance of the features is measured using Euclidean distance and given as input to Adaptive Resonance Theory (ART). The network is trained with an own dataset consisting of 70 facial images of various age group. The goal of the proposed work is to classify the human age group into four categories as Child, Adolescence, Adult and Senior Adult

An Expandable Drug Information Retrieval System for Oncology (EDIRS-FO)

Digitized for IUPUI ScholarWorks inclusion in 2021.Breast cancer was life threating a decade ago, however, now with the improvement in treatment the survival rate has increased considerably. Avoidable adverse effects accompany these treatments. The risk of acute and chronic adverse effects caused due to treatment greatly influence the quality of life in breast cancer survivors. An information system can reduce the avoidable ADR, thus, improving the decision making during patient encounters. It also makes the access to the information easier for the clinicians

Ontological Based CDSS in the Management of Breast Cancer

Digitized for IUPUI ScholarWorks inclusion in 2021.Accurate diagnosis is a key to ensure the most appropriate treatment. The diagnosis accuracy depends on physician's knowledge on the patient case. The ontological based CDSS is based on comprehending the diagnostic process and criteria to make accurate diagnosis and appropriate treatment plan

Sustainable reuse of magnesite mine tailings in cement-treated expansive soil for enhanced subgrade performance: geotechnical and environmental analysis

Abstract This study explores the use of Magnesite Mine Tailings (MMT) as an admixture in cement stabilization of Expansive Soil (ES) to improve subgrade performance and reduce environmental impact. Various combinations of Ordinary Portland Cement (OPC) and MMT were investigated using standard proctor compaction, Unconfined Compressive Strength (UCS), California Bearing Ratio (CBR), durability and Toxicity Characteristic Leaching Procedure (TCLP) tests. Results showed enhanced ES strength with MMT and OPC, with a maximum UCS of 1179 kPa and a soaked CBR of 25.1% after 28 days. However, higher cement content (>12%) is necessary for durability and meeting environmental regulations. X-Ray Diffraction and Field Emission Scanning Electron Microscopy confirmed hydration products, supporting MMT as a sustainable solution for stabilization and tailings disposal.Abstract This study explores the use of Magnesite Mine Tailings (MMT) as an admixture in cement stabilization of Expansive Soil (ES) to improve subgrade performance and reduce environmental impact. Various combinations of Ordinary Portland Cement (OPC) and MMT were investigated using standard proctor compaction, Unconfined Compressive Strength (UCS), California Bearing Ratio (CBR), durability and Toxicity Characteristic Leaching Procedure (TCLP) tests. Results showed enhanced ES strength with MMT and OPC, with a maximum UCS of 1179 kPa and a soaked CBR of 25.1% after 28 days. However, higher cement content (>12%) is necessary for durability and meeting environmental regulations. X-Ray Diffraction and Field Emission Scanning Electron Microscopy confirmed hydration products, supporting MMT as a sustainable solution for stabilization and tailings disposal

Kinetics and Mechanism of meso

Mechanistic study on meso-tetraphenylporphyrin iron(III) chloride (TPP) catalysed oxidation of indole-3-acetic acid by peroxomonosulphate (oxone) in aqueous acetonitrile medium has been carried out. The reaction follows a first order with respect to both substrate and oxidant. The order with respect to catalyst was found to be fractional. The order of reaction with respect to catalyst varies with a concentration of catalyst. Increase in percentage of acetonitrile decreased the rate. The reaction fails to initiate polymerization, and a radical mechanism is ruled out. Activation and thermodynamic parameters have been computed. A suitable kinetic scheme based on these observations is proposed. Significant catalytic activity is observed for the reaction system in the presence of TPP