Citation Impact
2.317 - 2-year Impact Factor
2.745 - 5-year Impact Factor
1.675 - Source Normalized Impact per Paper (SNIP)
0.908 - SCImago Journal Rank (SJR)
Usage
980,778 Downloads
1305 Altmetric mentions
Page 1 of 44
CPGs are not uniformly successful in improving care and several instances of implementation failure have been reported. Performing a comprehensive assessment of the barriers and enablers is key to developing a...
Citation: BMC Medical Informatics and Decision Making 2021 21:19
Access to and use of digital technology are more common among people of more advantaged socioeconomic status. These differences might be due to lack of interest, not having physical access or having lower inte...
Citation: BMC Medical Informatics and Decision Making 2021 21:18
Assessment of functional ability, including activities of daily living (ADLs), is a manual process completed by skilled health professionals. In the presented research, an automated decision support tool, the ...
Citation: BMC Medical Informatics and Decision Making 2021 21:17
Statistical data analysis, especially the advanced machine learning (ML) methods, have attracted considerable interest in clinical practices. We are looking for interpretability of the diagnostic/prognostic re...
Citation: BMC Medical Informatics and Decision Making 2021 21:16
The Coronavirus Disease 2019 (COVID-19) pandemic has infected over 10 million people globally with a relatively high mortality rate. There are many therapeutics undergoing clinical trials, but there is no effe...
Citation: BMC Medical Informatics and Decision Making 2021 21:15
Under the influences of chemotherapy regimens, clinical staging, immunologic expressions and other factors, the survival rates of patients with diffuse large B-cell lymphoma (DLBCL) are different. The accurate...
Citation: BMC Medical Informatics and Decision Making 2021 21:14
Videoconferencing has been proposed as a way of improving access to healthcare for older adults in care homes. Despite this, effective uptake of videoconferencing remains varied. This study evaluates a videoco...
Citation: BMC Medical Informatics and Decision Making 2021 21:13
Hospital-acquired pressure injuries (HAPrIs) are areas of damage to the skin occurring among 5–10% of surgical intensive care unit (ICU) patients. HAPrIs are mostly preventable; however, prevention may require...
Citation: BMC Medical Informatics and Decision Making 2021 21:12
The rapid growth of mobile technology has given rise to the development of mobile health (mHealth) applications aimed at treating and preventing a wide range of health conditions. However, evidence on the use ...
Citation: BMC Medical Informatics and Decision Making 2021 21:11
The nursing process is the core and the standard of practice in nursing profession. Nowadays, the use of information technology in the field of nursing processes, education and practice has been emphasized. Si...
Citation: BMC Medical Informatics and Decision Making 2021 21:10
Although ophthalmic devices have made remarkable progress and are widely used, most lack standardization of both image review and results reporting systems, making interoperability unachievable. We developed a...
Citation: BMC Medical Informatics and Decision Making 2021 21:9
The patient ranking process for donor lung allocation in the United States is carried out by a classification-based, computerized algorithm, known as the match system. Experts have suggested that a continuous,...
Citation: BMC Medical Informatics and Decision Making 2021 21:8
The cloud is a promising resource for data sharing and computing. It can optimize several legacy processes involving different units of a company or more companies. Recently, cloud technology applications are ...
Citation: BMC Medical Informatics and Decision Making 2021 21:7
The ability to report complete, accurate and timely data by HIV care providers and other entities is a key aspect in monitoring trends in HIV prevention, treatment and care, hence contributing to its eradicati...
Citation: BMC Medical Informatics and Decision Making 2021 21:6
Cardiovascular disease (CVD) is the leading cause of death in the United States (US). Better cardiovascular health (CVH) is associated with CVD prevention. Predicting future CVH levels may help providers bette...
Citation: BMC Medical Informatics and Decision Making 2021 21:5
Medication management processes in an Oncology setting are complex and difficult to examine in isolation from interrelated processes and contextual factors. This qualitative study aims to evaluate the usabilit...
Citation: BMC Medical Informatics and Decision Making 2021 21:4
Next-generation sequencing provides comprehensive information about individuals’ genetic makeup and is commonplace in oncology clinical practice. However, the utility of genetic information in the clinical dec...
Citation: BMC Medical Informatics and Decision Making 2021 21:3
Kidney transplant outcomes are broadly associated with transplant recipients’ capacity in following a complex and continuous self-management regimen. Health information technology has the potential to empower ...
Citation: BMC Medical Informatics and Decision Making 2021 21:2
Intrauterine Insemination (IUI) outcome prediction is a challenging issue which the assisted reproductive technology (ART) practitioners are dealing with. Predicting the success or failure of IUI based on the ...
Citation: BMC Medical Informatics and Decision Making 2021 21:1
Electronic health records (EHRs) offer various advantages for healthcare delivery, especially for chronic and complex diseases such as psoriasis. However, both patients’ and physicians’ acceptability is requir...
Citation: BMC Medical Informatics and Decision Making 2020 20:344
Electrocardiogram (ECG) signal, an important indicator for heart problems, is commonly corrupted by a low-frequency baseline wander (BW) artifact, which may cause interpretation difficulty or inaccurate analys...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):343
The 2020 International Conference on Intelligent Biology and Medicine (ICIBM 2020) provided a multidisciplinary forum for computational scientists and experimental biologists to share recent advances on all as...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):342
Age and time information stored within the histories of clinical notes can provide valuable insights for assessing a patient’s disease risk, understanding disease progression, and studying therapeutic outcomes...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):338
Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):322
When an Out-of-Hospital Cardiac Arrest (OHCA) incident is reported to emergency services, the 911 agent dispatches Emergency Medical Services to the location and activates responder network system (RNS), if th...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):313
The availability of massive amount of data enables the possibility of clinical predictive tasks. Deep learning methods have achieved promising performance on the tasks. However, most existing methods suffer fr...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):307
The collection and examination of social media has become a useful mechanism for studying the mental activity and behavior tendencies of users. Through the analysis of a collected set of Twitter data, a model ...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):304
Diabetes mellitus is a prevalent metabolic disease characterized by chronic hyperglycemia. The avalanche of healthcare data is accelerating precision and personalized medicine. Artificial intelligence and algo...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):295
Over 70% of Americans regularly experience stress. Chronic stress results in cancer, cardiovascular disease, depression, and diabetes, and thus is deeply detrimental to physiological health and psychological w...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 11):285
Sudden death in epilepsy (SUDEP) is a rare disease in US, however, they account for 8–17% of deaths in people with epilepsy. This disease involves complicated physiological patterns and it is still not clear w...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):330
Convolutional neural network (CNN) has achieved state-of-art performance in many electroencephalogram (EEG) related studies. However, the application of CNN in prediction of risk factors for sudden unexpected ...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):329
Applying machine learning to healthcare sheds light on evidence-based decision making and has shown promises to improve healthcare by combining clinical knowledge and biomedical data. However, medicine and dat...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):328
Sudden unexpected death in epilepsy (SUDEP) is a leading cause of premature death in patients with epilepsy. If timely assessment of SUDEP risk can be made, early interventions for optimized treatments might b...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):327
Sudden Unexpected Death in Epilepsy (SUDEP) has increased in awareness considerably over the last two decades and is acknowledged as a serious problem in epilepsy. However, the scientific community remains unc...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 12):326
The current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing fragmentation of information. To ensure...
Citation: BMC Medical Informatics and Decision Making 2020 20:341
Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management inform...
Citation: BMC Medical Informatics and Decision Making 2020 20:340
Routine Health Information Systems (RHIS) of low-income countries function below the globally expected standard, characterised by the production and use of poor-quality data, or the non-use of good quality dat...
Citation: BMC Medical Informatics and Decision Making 2020 20:339
Pneumothorax (PTX) may cause a life-threatening medical emergency with cardio-respiratory collapse that requires immediate intervention and rapid treatment. The screening and diagnosis of pneumothorax usually ...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):317
A various number of imaging modalities are available (e.g., magnetic resonance, x-ray, ultrasound, and biopsy) where each modality can reveal different structural aspects of tissues. However, the analysis of h...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):312
Automated summarization of scientific literature and patient records is essential for enhancing clinical decision-making and facilitating precision medicine. Most existing summarization methods are based on si...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):306
Ontologies house various kinds of domain knowledge in formal structures, primarily in the form of concepts and the associative relationships between them. Ontologies have become integral components of many hea...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):305
It is significant to model clinical activities for process mining, which assists in improving medical service quality. However, current process mining studies in healthcare pay more attention to the control fl...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):303
Increased chloride in the context of intravenous fluid chloride load and serum chloride levels (hyperchloremia) have previously been associated with increased morbidity and mortality in select subpopulations o...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):302
Biological and biomedical ontologies and terminologies are used to organize and store various domain-specific knowledge to provide standardization of terminology usage and to improve interoperability. The grow...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):301
Medical image data, like most patient information, have a strong requirement for privacy and confidentiality. This makes transmitting medical image data, within an open network, problematic, due to the aforeme...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 14):297
Summarization networks are compact summaries of ontologies. The “Big Picture” view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concep...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):296
Patients benefit from access to their medical records. However, clinical notes and letters are often difficult to comprehend for most lay people. Therefore, functionality was implemented in the patient portal ...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):278
While enrichment of terminologies can be achieved in different ways, filling gaps in the IS-A hierarchy backbone of a terminology appears especially promising. To avoid difficult manual inspection, we started ...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):272
The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):271
Dyadic-based social networks analyses have been effective in a variety of behavioral- and health-related research areas. We introduce an ontology-driven approach towards social network analysis through encodin...
Citation: BMC Medical Informatics and Decision Making 2020 20(Suppl 10):269
Citation Impact
2.317 - 2-year Impact Factor
2.745 - 5-year Impact Factor
1.675 - Source Normalized Impact per Paper (SNIP)
0.908 - SCImago Journal Rank (SJR)
Usage
980,778 Downloads
1305 Altmetric mentions