Bioinformatics is the field where computational methods from various domains have come together for analysis of biological data. Each domain has introduced its own specific jargon. However, in closely related domains, e.g. machine learning and statistics, concordant and discordant terminology occurs, the later can lead to confusion. This article aims to help solve the confusion of tongues arising from these two closely related domains, which are frequently used in bioinformatics. We provide a short summary of the most commonly applied machine learning and statistical approaches to data analysis in bioinformatics, i.e. classification and statistical hypothesis testing. We explain differences and similarities in common terminology used in various domains, such as precision, recall, sensitivity and true positive rate. This primer can serve as a guide to the terminology used in these fields.
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Background: Coronary heart disease (CHD) and depression frequently co-occur, significantly impacting patient outcomes. However, comprehensive health status assessment tools for this complex population are lacking. This study aimed to develop and validate an explainable machine learning model to evaluate overall health status in patients with comorbid CHD and depression.
View Article and Find Full Text PDFPsychoneuroendocrinology
January 2025
Department of Psychiatry, University of Michigan - Michigan Medicine, USA.
Prenatal stress has a well-established link to negative biobehavioral outcomes in young children, particularly for girls, but the specific timing during gestation of these associations remains unknown. In the current study, we examined differential effects of timing of prenatal stress on two infant biobehavioral outcomes [i.e.
View Article and Find Full Text PDFAnnu Rev Biomed Eng
January 2025
1School of Engineering, Brown University, Providence, Rhode Island, USA;
The rise in popularity of two-photon polymerization (TPP) as an additive manufacturing technique has impacted many areas of science and engineering, particularly those related to biomedical applications. Compared with other fabrication methods used for biomedical applications, TPP offers 3D, nanometer-scale fabrication dexterity (free-form). Moreover, the existence of turnkey commercial systems has increased accessibility.
View Article and Find Full Text PDFAnnu Rev Biomed Eng
January 2025
1Center for Engineering for Medicine and Surgery, Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA;
Gene therapy is a rapidly developing field, finally yielding clinical benefits. Genetic engineering of organs for transplantation may soon be an option, thanks to convergence with another breakthrough technology, ex vivo machine perfusion (EVMP). EVMP allows access to the functioning organ for genetic manipulation prior to transplant.
View Article and Find Full Text PDFJMIR Cancer
January 2025
Wolfson Institute of Population Health, Queen Mary University of London, London, United Kingdom.
Background: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals.
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