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Ovarian cancer is a serious malignant tumor threatening women’s health. The early diagnosis and effective treatments of ovarian cancer remain inadequate, and about 70% of ovarian cancers are in advanced stages...
Postnatal care, crucial for preventing and assessing complications after birth, remains low in India. An interactive mHealth community-based postnatal intervention was implemented to promote healthy maternal b...
This study aims at exploring a general and adaptive control strategy to confront the rapid evolution of an emerging infectious disease (‘Disease X’), drawing lessons from the management of COVID-19 in China. W...
We aimed to propose a deep-learning neural network model for automatically detecting five landmarks during a two-dimensional (2D) ultrasonography (US) scan to develop a standard plane for developmental dysplas...
Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus. Early identification of individuals at high risk of DPN is essential for successful early intervention. Traditional Ch...
The exponential growth in patient data collection by healthcare providers, governments, and private industries is yielding large and diverse datasets that offer new insights into critical medical questions. Le...
Migraine is a neurological disorder that affects millions of people worldwide. It is one of the most debilitating disorders which leads to many disability-adjusted life years. Conventional methods for investig...
Healthcare interventions are shaped by the resources needed to implement them, including staff time. This study, part of a process evaluation, aims to compare time spent on antenatal care (ANC) and related rec...
Unwanted random variability in day-to-day decision making referred to as ‘noise’ is associated with unhelpful variation that affects both the reproducibility and quality of decision making. Although this is de...
The clinical information housed within unstructured electronic health records (EHRs) has the potential to promote cancer research. The National Cancer Center Hospital (NCCH) is widely recognized as a leading i...
Identifying key variables is essential for developing clinical outcome prediction models based on high-dimensional electronic medical records (EMR). However, despite the abundance of feature selection (FS) met...
Depressive disorder, particularly major depressive disorder (MDD), significantly impact individuals and society. Traditional analysis methods often suffer from subjectivity and may not capture complex, non-lin...
De-identification of clinical notes is essential to utilize the rich information in unstructured text data in medical research. However, only limited work has been done in removing personal information from cl...
The diagnosis of pancreatic cancer presents a significant challenge due to the asymptomatic nature of the disease and the fact that it is frequently detected at an advanced stage. This study presents a novel a...
Ankle injuries in parcel delivery workers (PDWs) are most often caused by trips. Ankle sprains have high recurrence rates and are associated with chronic ankle instability (CAI). This study aimed to develop, d...
We recognized a paucity of accessible, evidence-based, empowering patient-centred resources for those with endometriosis-associated dyspareunia. Affecting more than 50% of people with endometriosis, dyspareuni...
The original article was published in BMC Medical Informatics and Decision Making 2025 25:27
Chronic Obstructive Pulmonary Disease (COPD) represents a significant global health challenge, placing considerable burdens on healthcare systems. The rise of digital health technologies (DHTs) and artificial ...
Despite substantial progress in maternal and neonatal health, Rwanda’s mortality rates remain high, necessitating innovative approaches to meet health related Sustainable Development Goals (SDGs). By leveragin...
The routine diagnostic process increasingly entails the processing of high-volume and high-dimensional data that cannot be directly visualised. This processing may provide scaling issues that limit the impleme...
Individuals with type 2 diabetes (T2D) have a high prevalence of cardiovascular and renal comorbidities. Despite clinical practice guidelines recommending the use of cardiorenal protective medications, many pe...
Despite recent progress in misinformation detection methods, further investigation is required to develop more robust fact-checking models with particular consideration for the unique challenges of health info...
Screening of malignant hematological diseases is of great importance for their diagnosis and subsequent treatment. This study constructed an optimal screening model for malignant hematological diseases based o...
This study proposes a deep learning-based motion assessment method that integrates the pose estimation algorithm (Keypoint RCNN) with signal processing techniques, demonstrating its reliability and effectivene...
Intraoperative imaging devices (i-ID), such as intraoperative optical coherence tomography (iOCT), offer surgeons critical insights previously unobservable, enhancing surgical precision and safety. Despite the...
This study aimed to develop a minimum dataset and an electronic registry system for hemodialysis patients to evaluate hemodialysis patients’ treatment procedures and outcomes, conduct related research, and des...
The original article was published in BMC Medical Informatics and Decision Making 2024 24:359
Agent negotiation is widely used in e-commerce negotiation, cloud service service-level agreements, and power transactions. However, few studies have adapted alternative negotiation models to negotiation proce...
In Japan, reporting of medical device malfunctions and related health problems is mandatory, and efforts are being made to standardize terminology through the Adverse Event Terminology Collection of the Japan ...
ECMO treatment for critically ill patients mostly requires family members to make surrogate decisions. However, the process and experience of family members’ participation in decision making have not been well...
Low birth weight (LBW) is a critical global health issue that affects infants disproportionately, particularly in developing countries. This study adopted causal machine learning (CML) algorithms for predictin...
The relevance of the study is due to the growing number of diseases of the cerebrovascular system, in particular stroke, which is one of the leading causes of disability and mortality in the world. To improve ...
Women diagnosed with breast cancer undergoing a mastectomy often have the option to undergo breast reconstruction (BR). BR decisions are complex and have considerable impact. We developed a patient decision ai...
Medical imaging techniques for diagnosing sarcopenia have been extensively investigated. Studies have proposed using the T-score and patient information as key diagnostic factors. However, these techniques hav...
Protecting digital health data from unauthorized access, alteration, and destruction is a crucial aspect of healthcare digitalization. Currently, digital security breaches are becoming more common. Healthcare ...
Virtual Gene Panels (VGP) comprising disease-associated causal genes are utilized in the diagnosis of rare genetic diseases to evaluate candidate genes identified by whole-genome and whole-exome sequencing. VG...
This article is part of a Supplement: Volume 25 Supplement 1
World is aging and the prevalence of chronic diseases is raising with age, increasing financial strain on organizations but also affecting patients’ quality of life until death. Research on healthcare trajecto...
Artificial intelligence (AI)-based systems are being rapidly integrated into the fields of health and social care. Although such systems can substantially improve the provision of care, diverse and marginalize...
Training machine learning models using data from severe COVID-19 patients admitted to a central hospital, where entire wards are specifically dedicated to COVID-19, may yield predictions that differ significan...
Patients with end-stage haemophilic arthritis (HA) are often hesitant about joint replacement surgery, yet little is known about the decision experiences faced by these patients. The aim of this study was to b...
Renal transplantation is a critical treatment for end-stage renal disease, but graft failure remains a significant concern. Accurate prediction of graft survival is crucial to identify high-risk patients. This...
Hypertension control remains a critical problem and most of the existing literature views it from a clinical perspective, overlooking the role of sociodemographic factors. This study aims to identify patients ...
England’s urgent care telephone triage system comprises non-clinician-led primary triage (NHS111) assessment followed, for approximately 50% patients, by clinician-led secondary triage. Digital decision suppor...
There is no effective way to accurately predict paroxysmal and persistent atrial fibrillation (AF) subtypes unless electrocardiogram (ECG) observation is obtained. We aim to develop a predictive model using a ...
Respiratory diseases and Cardiovascular Diseases (CVD) often coexist, with airflow obstruction (AO) severity closely linked to CVD incidence and mortality. As both conditions rise, early identification and int...
The aim of this study was to evaluate the potential models to determine the most important anthropometric factors associated with type 2 diabetes mellitus (T2DM).
This paper introduces SkinWiseNet (SWNet), a deep convolutional neural network designed for the detection and automatic classification of potentially malignant skin cancer conditions. SWNet optimizes feature e...
Postoperative pulmonary complications (PPCs) following cardiac valvular surgery are characterized by high morbidity, mortality, and economic cost. This study leverages wearable technology and machine learning ...
Type 1 diabetes (T1D) is a chronic endocrine disorder characterized by high blood glucose levels, impacting millions of people globally. Its management requires intensive insulin therapy, frequent blood glucos...
The original article was published in BMC Medical Informatics and Decision Making 2024 24:399
Citation Impact 2023
Journal Impact Factor: 3.3
5-year Journal Impact Factor: 3.9
Source Normalized Impact per Paper (SNIP): 1.304
SCImago Journal Rank (SJR): 1.002
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Submission to first editorial decision (median days): 9
Submission to acceptance (median days): 217
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