Big data medicine

BACKGROUND: Antenatal care (ANC) is one of the recommended interventions to reduce stillbirth, maternal, neonatal, and child mortality through early identification and management of pregnancy complications or pre-existing conditions. Although increasing number of ANC is a key priority of the 2016 WHO recommendations, ANC uptake in Low and Middle Income Countries (LMICs) is insufficient. Therefore, this study aimed to investigate factors associated with the number of ANC contacts in LMICs...

BACKGROUND: Given the urgency of transitioning towards sustainable nutrition, dietary shifts that provide co-benefits to human health and the environment are imperative. There is currently no database of the environmental impacts of foods that reflects Canada's unique geographical and agri-climatic context and regional inputs and emissions. To determine sustainable diets, harmonising nutritional considerations with environmental impacts is also essential for an equitable comparison of foods...

BACKGROUND: Digital health has been taught at medical faculties for a few years. However, in general, the teaching of digital competencies in medical education and training is still underrepresented. OBJECTIVE: This study aims to analyze the objective acquisition of digital competencies through the implementation of a transdisciplinary digital health curriculum as a compulsory elective subject at a German university. The main subject areas of digital leadership and management, digital learning and didactics, digital communication, robotics, and generative artificial intelligence were developed and taught in a transdisciplinary manner over a period of 1 semester...

BACKGROUND: Children form the most vulnerable strata of the society and the tobacco industry is known to target them. Article 16 of the Framework Convention of Tobacco Control (FCTC) calls for prohibition of tobacco sales to and by minors. Although interventions to stop such sales are based on sound science, it is widely acknowledged that many countries find implementation, full of challenges. In India, sales near educational institutions are banned by law, Section 6b of the Cigarettes & Other Tobacco Products Act (COTPA)...

Based on the analysis of data from listed enterprises in China between 2011 and 2022, we investigate the influence of digital transformation on the governance efficiency for minority shareholders. The results show that the extent of digital transformation exert a negative effect on the agency costs incurred from related-party transactions. The mechanism examination elucidates that digital transformation augments the governance efficiency for minority shareholders by boosting attendance at shareholders' meetings and enhancing the exit threat for minority shareholders...

The elderly population is growing rapidly in the world and falls are becoming a big problem for society. Currently, clinical assessments of gait and posture include functional evaluations, objective, and subjective scales. They are considered the gold standard to indicate optimal mobility and performance individually, but their sensitivity and specificity are not good enough to predict who is at higher risk of falling. An innovative approach for fall prediction is the machine learning. Machine learning is a computer-science area that uses statistics and optimization methods in a large amount of data to make outcome predictions...

BACKGROUND: To overcome the limitations of relying on data from a single institution, many researchers have studied data linkage methodologies. Data linkage includes errors owing to legal issues surrounding personal information and technical issues related to data processing. Linkage errors affect selection bias, and external and internal validity. Therefore, quality verification for each connection method with adherence to personal information protection is an important issue. This study evaluated the linkage quality of linked data and analyzed the potential bias resulting from linkage errors...

Personalized traditional Chinese medicine(TCM) preparations have entered a stage of rapid development. The key to the healthy development of this industry is to establish a sound manufacturing standard and quality control system. This paper analyzed the characteristics of personalized TCM preparations and drew reference from the quality management standards in the production of commissioned decoctions and oral pastes, on the basis of which the production quality management scheme and cautions for the safe production of personalized TCM preparations was put forward with consideration to various problems that may exist and occur in the production of such preparations...

In recent years, as people's living standards continue to improve, and the pace of life accelerates dramatically, the demand and quality of traditional Chinese medicine(TCM) services from patients continue to rise. As an essential supplement to the existing forms of TCM application, such as Chinese patent medicine, decoction, and formulated granules, presonalized TCM preparations is facing an increasing market demand. Currently, manual and semi-mechanized production are the primary production ways in presonalized TCM preparations...

Nanomanufacturing and digital manufacturing (DM) are defining the forefront of the fourth industrial revolution-Industry 4.0-as enabling technologies for the processing of materials spanning several length scales. This review delineates the evolution of nanomaterials and nanomanufacturing in the digital age for applications in medicine, robotics, sensory technology, semiconductors, and consumer electronics. The incorporation of artificial intelligence (AI) tools to explore nanomaterial synthesis, optimize nanomanufacturing processes, and aid high-fidelity nanoscale characterization is discussed...

Background: The use of AI-driven technologies in probing big data to generate better risk prediction models has been an ongoing and expanding area of investigation. The AI-driven models may perform better as compared to linear models; however, more investigations are needed in this area to refine their predictability and applicability to the field of durable MCS and cardiac transplantation. Methods: A literature review was carried out using Google Scholar/PubMed from 2000 to 2023. Results: This review defines the knowledge gaps and describes different AI-driven approaches that may be used to further our understanding...

Background: Influenza-like illness (ILI) encompasses symptoms similar to influenza, affecting population health. Surveillance, including Google Trends (GT), offers insights into epidemic patterns. Methods: This study used multiple regression models to analyze the correlation between ILI incidents, GT keyword searches, and climate variables during influenza outbreaks. It compared the predictive capabilities of time-series and deep learning models against ILI emergency incidents. Results: The GT searches for "fever" and "cough" were significantly associated with ILI cases ( p < 0...

The performance of the defect prediction model by using balanced and imbalanced datasets makes a big impact on the discovery of future defects. Current resampling techniques only address the imbalanced datasets without taking into consideration redundancy and noise inherent to the imbalanced datasets. To address the imbalance issue, we propose Kernel Crossover Oversampling (KCO), an oversampling technique based on kernel analysis and crossover interpolation. Specifically, the proposed technique aims to generate balanced datasets by increasing data diversity in order to reduce redundancy and noise...

This paper explores news media discourse about care.data: an NHS England programme of work for amalgamating and sharing patient data from primary care for planning and research. It was scrapped in 2016 after three years of public outcry, delays and around 1.5 million opt-outs. I examine UK news media coverage of this programme through the 'fire object' metaphor, focusing upon the visions of purpose and value it inspired, the abrupt discontinuities, juxtapositions and transformations it performed, and the matters of concern that went unheeded...

Climate change and its consequences are recognized as one of the most important challenges to the functioning of the Earth's ecosystem and humanity. However, the response to the threat posed by the climate crisis still seems inadequate. The question of which psychological factors cause people to engage (or not) in pro-environmental behavior remains without a comprehensive answer. The aim of this study is to establish the links between the cognitive (level of knowledge about climate change and degree of belief in climate myths), emotional (various climate emotions, especially climate anxiety) and behavioral aspects of attitudes towards the climate crisis and their determinants in the form of the Big Five personality domains and time perspectives...

The management of mechanical ventilation (MV) remains a challenge in intensive care units (ICUs). The digitalization of healthcare and the implementation of artificial intelligence (AI) and machine learning (ML) has significantly influenced medical decision-making capabilities, potentially enhancing patient outcomes. Acute respiratory distress syndrome, an overwhelming inflammatory lung disease, is common in ICUs. Most patients require MV. Prolonged MV is associated with an increased length of stay, morbidity, and mortality...

Obstructive sleep apnea (OSA) affects almost a billion people worldwide and is associated with a myriad of adverse health outcomes. Among the most prevalent and morbid are cardiovascular diseases (CVDs). Nonetheless, randomized controlled trials (RCTs) of OSA treatment have failed to show improvements in CVD outcomes. A major limitation in our field is the lack of precision in defining OSA and specifically subgroups with the potential to benefit from therapy. Further, this has called into question the validity of using the time-honored apnea-hypopnea index as the ultimate defining criteria for OSA...

Recent advancements in science and technology, coupled with the proliferation of data, have also urged laboratory medicine to integrate with the era of artificial intelligence (AI) and machine learning (ML). In the current practices of evidence-based medicine, the laboratory tests analysing disease patterns through the association rule mining (ARM) have emerged as a modern tool for the risk assessment and the disease stratification, with the potential to reduce cardio-vascular disease (CVD) mortality. CVDs are the well recognised leading global cause of mortality with the higher fatality rates in the Indian population due to associated factors like hypertension, diabetes, and lifestyle choices...

BACKGROUND: Physical exercise is effective in managing Parkinson's disease (PD), but the relative benefit of different exercise types remains unclear. OBJECTIVES: To compare the effects of different types of physical exercise in adults with PD on the severity of motor signs, quality of life (QoL), and the occurrence of adverse events, and to generate a clinically meaningful treatment ranking using network meta-analyses (NMAs). SEARCH METHODS: An experienced information specialist performed a systematic search for relevant articles in CENTRAL, MEDLINE, Embase, and five other databases to 17 May 2021...

Artificial intelligence (AI) has extensive applications in a wide range of disciplines including healthcare and clinical practice. Advances in high-resolution whole-slide brightfield microscopy allow for the digitization of histologically stained tissue sections, producing gigapixel-scale whole-slide images (WSI). The significant improvement in computing and revolution of deep neural network (DNN)-based AI technologies over the last decade allow us to integrate massively parallelized computational power, cutting-edge AI algorithms, and big data storage, management, and processing...