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Full-Text Articles in Medicine and Health Sciences
Provider Perceptions Of Virtual Reality As A Therapeutic Tool, Margaret Eberts, Christine Vincent, Tejal U. Naik, Md, Virginia O'Hayer
Provider Perceptions Of Virtual Reality As A Therapeutic Tool, Margaret Eberts, Christine Vincent, Tejal U. Naik, Md, Virginia O'Hayer
Phase 1
Introduction: Virtual reality (VR) shows significant potential as a healthcare tool, especially in the management of anxiety disorders and pain. However, despite recent studies demonstrating the effectiveness of VR, there continues to be limited use among providers. A lack of resources and understanding of the feasibility of clinical VR use may present a significant barrier for VR implementation. Through studying the perceptions of providers using VR clinically, this study aims to understand the achievability of VR as a standardized therapy.
Methods: Researchers distributed an online, self-administered questionnaire to healthcare providers identified on VR application websites. The questionnaire consisted of five …
Cryo Vs Rf P-Wave Characteristics Comparative Analysis, John Schanz, Waleed Khan, Behzad B. Pavri
Cryo Vs Rf P-Wave Characteristics Comparative Analysis, John Schanz, Waleed Khan, Behzad B. Pavri
Phase 1
Introduction: Atrial fibrillation (AF) is the leading cause of stroke. Patients with drug-refractory AF are managed with Radiofrequency (RF) or Cryoballoon (Cryo) pulmonary vein isolation (PVI). Approximately 30% of PVIs result in AF recurrences. There is clinical utility in identifying patients at higher risk of AF recurrence with readily available ECG parameters.
Methods: This retrospective study analyzed the ECG characteristics and AF recurrence of 86 paroxysmal AF patients who underwent PVI. Baseline characteristics were collected by chart review and p-wave parameters were measured with electronic calipers in the MUSE (GE) ECG database. AF recurrence was defined as any documented atrial …
Impact Of Algorithmic Bias On Hospital Risk Stratification Scores Among Insurance Recipients, Andrew Zeiger, Victoria Gulick, Tejal U. Naik
Impact Of Algorithmic Bias On Hospital Risk Stratification Scores Among Insurance Recipients, Andrew Zeiger, Victoria Gulick, Tejal U. Naik
Phase 1
Introduction: Although medical schools are implementing programs to promote student scholarship, few programs exist to informally promote inter-student collaboration. Considering many medical students are early in the process of deciding what they want to spend their lives pursuing, and high levels of social connection and engagement may reduce burnout, we sought to evaluate medical students’ attitudes about inter-student collaboration.
Methods: Approximately 1000 medical students in all classes at Sidney Kimmel Medical College (SKMC) were invited to complete a questionnaire. Data collection remains active. Survey questions included a rank order choice on how respondents would use a tool to learn about …
Provider Perceptions Of Virtual Reality As A Therapeutic Tool, Christine Vincent, Margaret Eberts, Tejal U. Naik, C. Virginia O'Hayer
Provider Perceptions Of Virtual Reality As A Therapeutic Tool, Christine Vincent, Margaret Eberts, Tejal U. Naik, C. Virginia O'Hayer
Phase 1
Introduction: Virtual reality (VR) can be an effective healthcare tool, particularly applied to anxiety and pain management. Despite significant interest in VR, lack of resources and knowledge regarding feasibility are barriers to implementation. This study aims to understand the current clinical usage of VR and the achievability of VR as a standardized therapy, by assessing VR healthcare providers.
Methods: An online, self-administered questionnaire with five sections—respondent demographics, VR value, onboarding, billing, and clinical use—was distributed. Providers, identified on VR application websites, were contacted via email. Inclusion criteria was providers in the United States using VR actively or in the past …
Readmission Risk Assessment Tool For Stroke Patients, Simran Rahi, Sasha Mitts, Dominick Battistini, Tiffany D’Souza, Bryan Sadler, Krista Mar, Maureen Deprince, Deborah Murphy, Diana Tzeng, Md
Readmission Risk Assessment Tool For Stroke Patients, Simran Rahi, Sasha Mitts, Dominick Battistini, Tiffany D’Souza, Bryan Sadler, Krista Mar, Maureen Deprince, Deborah Murphy, Diana Tzeng, Md
Phase 1
Introduction: Strokes are one of the leading causes of morbidity and mortality in the world and its cost of management has vastly increased; an effective prediction tool that utilizes artificial intelligence to lower the rate of stroke-related readmissions has the potential to lower healthcare costs and increase the quality of provider care. We hypothesize that machine learning techniques are superior to traditional statistics when determining the likelihood of 30-day readmission for Jefferson’s stroke patients.
Methods: Jefferson’s existing data on stroke patients were cleaned, aggregated, and prepared to be split into train and test sets. Using the train sets, machine learning …
Machine Learning Models For 6-Month Survival Prediction After Surgical Resection Of Glioblastoma, Jeffrey Gray, Lohit Velagapudi, Michael Baldassari, Bryan Sadler, David Vuong
Machine Learning Models For 6-Month Survival Prediction After Surgical Resection Of Glioblastoma, Jeffrey Gray, Lohit Velagapudi, Michael Baldassari, Bryan Sadler, David Vuong
Phase 1
Introduction: The role of surgical resection for the treatment of glioblastoma multiforme is well established. Survival analysis after resective surgery in the literature comprises mostly of traditional statistical models. Machine learning models offer powerful predictive and analytical capability for varied datasets and offer improved generalizability and scalability. We analyzed survival data of patients with glioblastoma with various machine learning algorithms and compared it to binary logistic regression.
Methods: We retrospectively identified cases of glioblastoma treated with surgical resection at our institution from 2012-2018. Feature scaling and one-hot encoding was used to better fit the models to the data and used …
Patient Tolerance To Virtual Reality-Based Vestibular Rehabilitation: A Scoping Review, Michael Knapp, Tejal Naik
Patient Tolerance To Virtual Reality-Based Vestibular Rehabilitation: A Scoping Review, Michael Knapp, Tejal Naik
Phase 1
Introduction: Virtual reality-based therapy (VRBT) using head-mounted devices (HMDs) is being explored as a novel treatment modality for rehabilitation of vestibular disorders. We hypothesize there may exist unique risks and side effects to VRBT using HMDs in the vestibular patient population which no previous studies have directly explored. This scoping review compiles all currently published data concerning vestibular patient tolerance to this treatment modality and provides preliminary interpretation of overall risks.
Methods: An exhaustive list of search terms covering virtual reality, HMDs, vestibular disorders, side effects, and adverse events were submitted to six different databases. Returned papers were uploaded to …
Detecting Anterior Cruciate Ligament Tears And Posterolateral Corner Injuries On Magnetic Resonance Imaging, Paul Woloszyn, Vishal Desai, Md, Simukayi Mutasa, Md, Tiffany D’Souza, Dominick Battistini, Sasha Mitts, Bryan Sadler
Detecting Anterior Cruciate Ligament Tears And Posterolateral Corner Injuries On Magnetic Resonance Imaging, Paul Woloszyn, Vishal Desai, Md, Simukayi Mutasa, Md, Tiffany D’Souza, Dominick Battistini, Sasha Mitts, Bryan Sadler
Phase 1
Introduction: Anterior Cruciate Ligament (ACL) tears are an extremely common orthopedic injury, with an incidence ranging from 39-52 per 100,000. Knee Magnetic Resonance Imaging (MRI) scans are the gold standard for diagnosing ACL tears and their comorbidities, such as posterolateral corner injuries; the results of these scans determine the appropriate treatment needed for patients. There is evidence that machine learning can be used to automate the detection of pathology on MRI, and we hypothesize that we can train a neural network machine learning model to accurately interpret ACL injuries and posterolateral corner injuries.
Methods: We will be analyzing over 1000 …
Creation Of A Web-Based Tool To Facilitate Community Connectivity, Peter Zdunek, Sarah Reed, Saima Anis, J. Alex Wrem
Creation Of A Web-Based Tool To Facilitate Community Connectivity, Peter Zdunek, Sarah Reed, Saima Anis, J. Alex Wrem
Phase 1
Introduction: Artificial intelligence-based modelling has created an opportunity to improve upon existing hospital readmission risk score systems by redefining priority and uncovering new criteria, but inherent systematic errors known as algorithmic bias can impact applicability. This study evaluated whether there is racial bias for unplanned readmission risk scores in a novel model prepared for the CMS AI challenge.
Methods: The study population provided by the CMS challenge included Medicare recipients from 2012 (unique beneficiaries n=1,667,362, total claims n=34,233,260). Risk scores for unplanned hospital readmissions were projected on the basis of clinical and demographic criteria, including age, sex, comorbidities, and prior …