Tick parasitism classification from noisy medical records

Much of the health information in the medical domain comes in the form of clinical narratives. The rich semantic information contained in these notes can be modeled to make inferences that assist the decision making process for medical practitioners, which is particularly important under time and resource constraints. However, the creation of such assistive tools is made difficult given the ubiquity of misspellings, unsegmented words and morphologically complex or rare medical terms. This reduces the coverage of vocabulary terms present in commonly used pretrained distributed word representations that are passed as input to parametric models that makes such predictions. This paper presents an ensemble architecture that combines indomain and general word embeddings to overcome these challenges, showing best performance on a binary classification task when compared to various other baselines. We demonstrate our approach in the context of the veterinary domain for the task of identifying tick parasitism from small animals. The best model shows 84.29% test accuracy, showing some improvement over models, which only use pretrained embeddings that are not specifically trained for the medical sub-domain of interest

An ontology co-design method for the co-creation of a continuous care ontology

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented

Assessing Professionalism: A theoretical framework for defining clinical rotation assessment criteria

Although widely accepted as an important graduate competence, professionalism is a challenging outcome to define and assess. Clinical rotations provide an excellent opportunity to develop student professionalism through the use of experiential learning and effective feedback, but without appropriate theoretical frameworks, clinical teachers may find it difficult to identify appropriate learning outcomes. The adage “I know it when I see it” is unhelpful in providing feedback and guidance for student improvement, and criteria that are more specifically defined would help students direct their own development. This study sought first to identify how clinical faculty in one institution currently assess professionalism, using retrospective analysis of material obtained in undergraduate teaching and faculty development sessions. Subsequently, a faculty workshop was held in which a round-table type discussion sought to develop these ideas and identify how professionalism assessment could be improved. The output of this session was a theoretical framework for teaching and assessing professionalism, providing example assessment criteria and ideas for clinical teaching. This includes categories such as client and colleague interaction, respect and trust, recognition of limitations, and understanding of different professional identities. Each category includes detailed descriptions of the knowledge, skills, and behaviors expected of students in these areas. The criteria were determined by engaging faculty in the development of the framework, and therefore they should represent a focused development of criteria already used to assess professionalism, and not a novel and unfamiliar set of assessment guidelines. The faculty-led nature of this framework is expected to facilitate implementation in clinical teaching