Many people in the United States and internationally have health problems linked to, or amplified by, their dietary choices. Continued research into user-centered design methodologies and the microbiome paves the way for greater accessibility of translational science's movement from laboratory settings to clinical applications for enhancing human health through nutritional interventions. This survey explored recent literature examining how nutrition interacts with the microbiome, using informatics approaches.
Recent literature was synthesized in this survey to illustrate how technology is used to understand health, specifically at the consumer level, within the interplay of nutrition and the microbiome.
From January 1, 2021, to October 10, 2022, a review of publications was undertaken utilizing PubMed, and the discovered literature was subjected to an assessment according to pre-defined inclusion and exclusion criteria.
One hundred thirty-nine papers were obtained and evaluated against the benchmarks for inclusion and exclusion. pacemaker-associated infection Upon assessment, 45 papers underwent a detailed review, culminating in the identification of four key themes: (1) microbiome and dietary interactions, (2) user-friendliness, (3) reproducibility and research rigor, and (4) precision medicine and precision nutrition strategies.
A critical evaluation of the literature on the interplay between technology, nutritional science, the microbiome, and the self-management of dietary regimens was performed. A captivating array of themes arose from this survey, highlighting innovative approaches to consumer dietary management and disease, as well as significant steps toward deciphering the intricate relationship between diet, the microbiome, and health results. The survey confirmed ongoing interest in the microbiome and diet-related diseases, accompanied by the necessity for equitable and rigorous methods of measuring the microbiome and for sharing and re-using data. The literature points to a rising trend in enhancing digital tools' usability for consumer health and home management, and a growing consensus concerning the future implementation of precision medicine and nutrition in improving human health outcomes and preventing diet-related illnesses.
Current research on technology, nutrition, the microbiome, and the self-governance of dietary choices was surveyed and assessed. Emerging themes from the survey showcase exciting potential for consumer control over diet and disease, alongside advancements in the understanding of how diet, the microbiome, and health are interrelated. The survey revealed a persistent interest in diet-related diseases and the microbiome, coupled with a recognition of the essential need for unbiased and rigorous methods for microbiome measurement, data sharing, and data re-use. Research literature indicated an evolving trend towards increasing the accessibility of digital tools for consumer health and home management, and a unifying perspective on how precision medicine and precision nutrition could potentially be used to optimize health outcomes and prevent diet-related diseases in the future.
Despite the increasing excitement about the use of clinical informatics to enhance cancer outcomes, a persistent shortage of readily available data remains a crucial impediment. The intricate task of integrating protected health information with data frequently hinders the creation of comprehensive, representative datasets for analysis. The rise of machine learning methods, requiring ever-larger clinical datasets, has led to a corresponding increase in these constraints. This paper scrutinizes recent advancements in clinical informatics for the safe exchange of cancer data.
A narrative review of clinical informatics studies pertaining to protected health data sharing within cancer research, conducted from 2018 to 2022, examined topics like decentralized analytics, homomorphic encryption, and standard data models.
Identified were clinical informatics studies dedicated to examining the sharing of cancer data. A concentrated search yielded insightful studies on decentralized analytics, homomorphic encryption, and common data models. Within the realm of decentralized analytics, genomic, imaging, and clinical data have been prototyped; diagnostic image analysis displays the most advancement. Homomorphic encryption saw its most common use case in the handling of genomic data, while its application to imaging and clinical data was less prevalent. Electronic health records serve as the principal source of clinical data employed in common data models. Despite the robust research underpinning each approach, the extent of large-scale implementation is scarcely documented.
Common data models, homomorphic encryption, and decentralized analytics hold the potential to significantly improve the sharing of cancer data. The hopeful results attained so far are restricted to smaller-scale operations. Further studies should explore the feasibility and effectiveness of applying these methods in different clinical environments, acknowledging the varying levels of resources and expertise.
Homomorphic encryption, decentralized analytics, and common data models are promising strategies for advancing the sharing of cancer data. Up to now, encouraging outcomes have been observed primarily in smaller contexts. Further studies should concentrate on measuring the scalability and efficacy of these procedures within diverse clinical settings, varying in the levels of resources and expertise.
One Health promotes a more comprehensive and interconnected approach to understanding the interdependence of human health and the environment. Digital health plays a vital role in supporting both healthcare practitioners and the general public. One Digital Health (ODH) leverages the technological aspects of both One Health and Digital Health to provide a unified view. ODH views the environment and ecosystems as fundamentally significant. Subsequently, the development and implementation of health technologies, including digital health platforms, should be guided by principles of environmental responsibility and eco-friendliness to the greatest degree possible. This position paper offers examples of developing and implementing ODH-related concepts, systems, and products, with due regard for the environment. The importance of developing advanced technologies to improve the healthcare and wellness of both humans and animals cannot be overstated. Nevertheless, the One Health paradigm compels us to architect One Digital Health, one that will integrate environmentally sound, green, and socially responsible procedures.
Through reflective considerations, guidance is offered regarding the upcoming development and role of medical informatics, or biomedical and health informatics.
The author's impressive medical informatics background, stretching across almost half a century, is documented. It was in 1973 that he embarked on his studies of medical informatics. His professional path, initiating in 1978, stretches over four decades. His professional tenure concluded with the final day of the 2021 summer semester. This event was the perfect opportunity to prepare this final lecture.
Considered in twenty reflections are professional careers (R1 – 'places'), medical informatics (R2 – 'interdisciplinarity', R3 – 'focuses', R4 – 'affiliations'), research (R5 – 'duality', R6 – 'confluences', R7 – 'correlations', R8 – 'collaboration'), education (R9 – 'community', R10 – 'competencies', R11 – 'approaches'), academic autonomy (R12 – 'autonomy'), engagement (R13 – 'Sisyphos', R14 – 'professional societies', R15 – 'respect', R16 – 'tightrope walk'), and good scientific practice (R17 – 'time invariants', R18 – 'Zeitgeist', R19 – 'knowledge gain', R20 – 'exercising').
Participating in medical informatics activities for nearly five decades has been a genuine pleasure for me. Within this period, considerable advancements have been achieved in various fields, notably in medicine and informatics, and, importantly, within medical informatics Now, others take their place. While acknowledging that tradition sustains not the ashes, but the flame, this report, with its thoughtful reflections, might prove beneficial.
My involvement in medical informatics activities has brought me immense pleasure over the last almost fifty years. Significant advancements have occurred during that time, notably within the realms of medicine, informatics, and medical informatics itself. Others are now due a turn. Monogenetic models Remembering that tradition involves the passage of inspiration, not the remnants, this report, including its insightful reflections, may contribute to a better understanding.
A substantial portion of the global population, approximately 30 to 40 percent, experiences nonalcoholic fatty liver disease (NAFLD), which is increasingly viewed as the most common liver ailment. Those with type 2 diabetes, obesity, and cardiovascular diseases are exceptionally predisposed to NAFLD. Though most patients with NAFLD experience a benign course of their liver condition, some unfortunately experience disease progression leading to cirrhosis, liver cancer, and liver-related mortality. TTK21 in vivo In view of the considerable number of patients suffering from NAFLD, the disease's impact is undoubtedly a major concern. Despite the increasing and considerable weight of NAFLD, a reliable identification of patients at risk for progressive liver disease in primary care and diabetology settings remains remarkably suboptimal. This review outlines a sequential method for classifying NAFLD patients by risk, aiming to assist practitioners in managing these cases.
The increased intricacy of patient care for hepatocellular carcinoma is a result of the advancements in surgical and systemic treatment approaches. A dynamic adjustment of the existing staging-based algorithms is essential for enabling adaptable therapeutic allocation. In particular, hepatocellular carcinoma management in the real world is increasingly dependent on factors beyond cancer stage, such as patient frailty, comorbidities, the tumor's location within the liver, diverse liver function assessments, and specific technical limitations affecting treatment delivery and resource access.