Cancer is molecularly heterogeneous, with seemingly similar patients having different molecular landscapes and accordingly different clinical behaviors. In recent studies, gene expression networks hav...
Healthcare costs have dramatically increased, resulting in barriers to care for many Americans. To address this, the Centers for Medicare & Medicaid Services implemented a price transparency mandate, ...
Cost transparency was investigated using cost-estimate tools from websites of the seven New England hospitals ranked on the US News top 50 list. Ten common current procedural terminology codes were us...
All investigated hospitals had cost-estimate tools, with a 35.7 % mean success rate of generating an estimate. The mean times to cost-estimate tools and generated estimates were 35.69 and 34.15 s, res...
All hospitals complied with the Centers for Medicare & Medicaid Services price transparency policy. The information available is sparse, difficult to access, and frequently lacks specific estimates fo...
Diagnostic stewardship is 'coordinated guidance and interventions to improve appropriate use of microbiological diagnostics to guide therapeutic decisions' and a fundamental part of antimicrobial stew...
To determine the role of the hospital adult nurse in diagnostic stewardship to inform local engagement strategies....
The methodology was informed by Whiffin's (2020) systematic search approach. Electronic databases were searched from 2016 to 2022. The studies included were primary research papers involving adult nur...
Seven studies were included in the review. The identified themes were: (i) nursing role - to recognize infection, aid diagnosis and review results; (ii) nurse challenges - lack of knowledge and confid...
Research studies do not consistently recognize the full scope of the diagnostic stewardship nursing role, signifying that nurses remain an underused resource in promoting diagnostic stewardship. Resea...
Machine learning models are vital for enhancing healthcare services. However, integrating them into health information systems (HISs) introduces challenges beyond clinical decision making, such as int...
The MoCab architecture is designed to streamline predictive modeling in healthcare through a structured framework incorporating several specialized parts. The Data Service Center manages patient data ...
The MoCab framework was demonstrated using three types of predictive models: a scoring model (qCSI), a machine learning model (NSTI), and a deep learning model (SPC), applied to synthetic data that mi...
We demonstrate MoCab's potential in promoting the interoperability of machine learning models and enhancing its utility across various EHRs. Despite facing challenges like FHIR adoption, MoCab address...
In the emergency departments (EDs), usually the longest waiting time for treatment and discharge belongs to the elderly patients. Moreover, the number of the ED admissions for the elderly increases ev...
This study was conducted in 2021. The initial conceptual model was designed based on the findings derived from the previous research phases (literature review and interview with the experts). Then, th...
The common information technologies appropriate for the elderly care in the emergency departments included emergency department information system, clinical decision support system, electronic health ...
The proposed model can help to design and implement the most useful information systems in the geriatric emergency departments. As the application of technology accelerates care processes, investing i...
SLAM is a critical technology for enabling autonomous navigation and positioning in unmanned vehicles. Traditional visual simultaneous localization and mapping algorithms are built upon the assumption...
Understanding the multifaceted nature of health outcomes requires a comprehensive examination of the social, economic, and environmental determinants that shape individual well-being. Among these dete...
Traditional natural language processing (NLP) methods face limitations in accurately parsing diverse clinical language associated with substance use. Large Language Models (LLMs) offer promise in over...
The main data source for analysis in this paper is Medical Information Mart for Intensive Care III (MIMIC-III) dataset. Among all notes in this dataset, we focused on discharge summaries. Prompt engin...
The presented results highlight the contrasting performance of GPT in extracting text span mentioning tobacco, alcohol, and substance use in both zero-shot and few-shot learning scenarios. In the zero...
Excellence of zero-shot learning in precisely extracting text span mentioning substance use demonstrates its effectiveness in situations where comprehensive recall is important. Conversely, few-shot l...
Weight management mobile applications have become increasingly popular as a tool for individuals to achieve their weight loss goals. However, key challenges with mobile weight management applications ...
We conducted face-to-face interviews with five experts to evaluate and give input on the proposed framework....
Eight specialized functionalities have been categorized and defined based on initial framework system features and recommended features based on experts' feedback: (I) customization; (II) usability; (...
These functionalities and features will be incorporated into a framework to design mobile applications for sustainable weight management. Also, to be part of user interface development for the user ex...
Community-based palliative care (CBPC) clinicians sometimes contend with an ethically charged scenario when they encounter patients for the first time: The patient's spouse, or other loved one or care...
