Short-term impact of COVID-19 on quality of life,perceived stress,and serious psychological distress in an adult population in the midwest United States

Quality of Life Research - This study aimed to investigate changes over time in quality of life, perceived stress, and serious psychological distress for individuals diagnosed with COVID-19 in an...     

Clinical Concept-Based Radiology Reports Classification Pipeline for Lung Carcinoma

Rising incidence and mortality of cancer have led to an incremental amount of research in the field. To learn from preexisting data, it has become important to capture maximum information related to disease type, stage, treatment, and outcomes. Medical imaging reports are rich in this kind of information but are only present as free text. The extraction of information from such unstructured text reports is labor-intensive. The use of Natural Language Processing (NLP) tools to extract information from radiology reports can make it less time-consuming as well as more effective. In this study, we have developed and compared different models for the classification of lung carcinoma reports using clinical concepts. This study was approved by the institutional ethics committee as a retrospective study with a waiver of informed consent. A clinical concept-based classification pipeline for lung carcinoma radiology reports was developed using rule-based as well as machine learning models and compared. The machine learning models used were XGBoost and two more deep learning model architectures with bidirectional long short-term neural networks. A corpus consisting of 1700 radiology reports including computed tomography (CT) and positron emission tomography/computed tomography (PET/CT) reports were used for development and testing. Five hundred one radiology reports from MIMIC-III Clinical Database version 1.4 was used for external validation. The pipeline achieved an overall F1 score of 0.94 on the internal set and 0.74 on external validation with the rule-based algorithm using expert input giving the best performance. Among the machine learning models, the Bi-LSTM_dropout model performed better than the ML model using XGBoost and the Bi-LSTM_simple model on internal set, whereas on external validation, the Bi-LSTM_simple model performed relatively better than other 2. This pipeline can be used for clinical concept-based classification of radiology reports related to lung carcinoma from a huge corpus and also for automated annotation of these reports.

     

Synthesis of diversely substituted bis-pyrrolizidino/ thiopyrrolizidino oxindolo/acenaphthyleno curcuminoids via sequential azomethine ylide cycloaddition

Curcumin has been transformed to several diversely substituted bis-pyrrolizidino/thiopyrrolizidino oxindolo/acenaphthyleno curcuminoids via a sequential azomethine ylide cycloaddition reaction using isatins/acenaphthoquinone and proline/thioproline as the reagents. The products were separated via extensive chromatography and characterized by 1D/2D NMR and HRMS analysis.

Curcumin has been transformed to several diversely substituted bis-pyrrolizidino/thiopyrrolizidino oxindolo/acenaphthyleno curcuminoids via a sequential azomethine ylide cycloaddition reaction.     

Novel CD3Z and CD3E Deficiency in Two Unrelated Females

Journal of Clinical Immunology -     

Neuroanatomical associations of the Edinburgh cognitive and Behavioural ALS screen (ECAS)

Brain Imaging and Behavior - Cognitive impairment is now recognized in a subset of patients with amyotrophic lateral sclerosis (ALS). The objective of the study was to identify group differences...     

User profiles and personas in the design and development of consumer health technologies

Background“The graying of the globe” has resulted in exponential rise in health care expenses, over-worked health care professionals and a growing patient base suffering from multiple chronic diseases, one of which is diabetes. Consumer health technologies (CHT) are considered important catalysts for empowering health care consumers to take a proactive role in managing their health and related costs. Adoption rate and usability of such devices among the aging is far from being satisfactory. Past studies noted the motivation for adoption by the aging is dependent on the suitability/relevance, perceived usability and anticipated benefits associated with usage of technological innovation. Traditional information technology (IT) development adopts a systematic approach without necessarily using a specific user model that personalizes the system to the aging user groups. The aging patient population has unique needs arising from progressive deterioration in both physiological and psychological abilities. These needs are often ignored in the design, development, trial and adoption of consumer health products resulting in low adoption and usage.ObjectivesThe main objective of this research is to investigate the user-centered design (UCD), specifically user profiles and personas, as methodological tools to inform the design and development of CHT devices for an aging population. The adoption of user profile and persona has not received much attention in health care informatics research and, in particular, research involving CHT. Our work begins to fill this void in three ways. We (1) illuminate the process of developing CHT user profiles and personas for a Chinese elder population with a demanding health care needs, i.e., self-management of chronic diabetes, with the hope that the resulting profiles and personas may be used as foundational material for informing the design, development and evaluation of CHT in other similar contexts; (2) call attention to how to further enhance and complement traditional user profile and persona techniques for CHT design by integrating cognitive structures and present behavior that drive health care thinking, future behavior and demand; (3) show how the profiles and personas can be used to inform requirements, design and implementation decisions for a technology aimed at facilitating CHT adoption and diffusion for the elderly.MethodologyTo exemplify process and application, we use an action-research methodology, where user profiles and personas of an aging patient population were developed. The resultant profiles and personas were leveraged to improve the design, development and implementation plans of a smart phone application to assist chronically ill aging Chinese diabetic population capable of disease self-management.ResultsThe results from the study show that user profile and persona can be a valuable methodological approach in capturing the conceptual model of the aging and informing the design and development decisions of CHT. The demonstration of techniques used in this study can serve as a guideline to CHT developers in bringing conceptual user modeling into the design of software interfaces targeted for users with specific health care needs. Specifically, the study provides guidance on the creation and use of profiles and personas to tap into the conceptual models of the targeted elderly population reflecting their preferences, capabilities and attitudes towards using technology in self-management care in general and the smart phone diabetes management application in particular. Insight into the mental model of the aging group has been shown to inform later stages of UCD development (e.g., the creation of prototypes and usability testing) as well as implementation and adoption strategies. The World Health Organization (WHO) predicts that by 2025, 80% of all new cases of diabetes are expected to appear in the developing countries. In fact, the number of diabetic patients in China is estimated to rise to 42.3 million in 2030 from 20.8 million in 2000. Thus, we investigate the Chinese aging population in order to demonstrate the process of developing and using user profile and persona. We hope that the resultant conceptual model of the Chinese aging diabetic population can be used in future research to guide CHT designers interested in designing health care devices for this vulnerable user group.