Two major trends have been dominant in health care in recent years. First, there is a growing consensus that standardization of health care procedures and methods can result in improved effectiveness and safety of treatments. Second, there is increased interest in "personalized medicine," which refers to the tailoring of treatments to individual patients. Here I discuss how these trends apply to the field of quantitative EEG (qEEG), where de-artifacted resting state EEGs of individuals are compared with a normative database in order to assess clinically meaningful deviations, which can be used for diagnostic procedures, to guide personalized treatment protocols, and to assess treatment effectiveness. Standardized and automated de-artifacting procedures are increasingly being used in scientific research and in clinical practice. The advantages of these procedures over manual de-artifacting will be discussed. The results of a systematic comparison between 2 commonly used qEEG databases show that these databases produce very comparable results, illustrating not only the validity and reliability of both databases but also the opportunity to move forward to a standardized use of qEEG in clinical practice. Finally, the standardization of qEEG interpretation as both a diagnostic and treatment selection tool provides an example of how qEEG can merge both personalized medicine and standardization in the treatment of psychological disorders.
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Biomed Phys Eng Express
January 2025
Radiation Oncology, Emory University, Emory Midtown Hospital, Atlanta, Georgia, 30322, UNITED STATES.
Although radiotherapy techniques are the primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity, and side effect. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on features extracted from pre-treatment imaging data. This study aims to compare different models in predicting radiation-induced xerostomia and sticky saliva in both early and late stage of HNC patients using CT and MRI image features along with demographics and dosimetric information.
View Article and Find Full Text PDFHepatology
January 2025
Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA.
Background Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects about a third of adults worldwide and is projected soon to be the leading cause of cirrhosis. It occurs when fat accumulates in hepatocytes and can progress to metabolic dysfunction-associated steatohepatitis (MASH), liver cirrhosis, and hepatocellular carcinoma. MASLD pathogenesis is believed to involve a combination of genetic and environmental risk factors.
View Article and Find Full Text PDFAnnu Rev Biomed Data Sci
January 2025
1Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, California, USA;
Cancer remains a leading cause of death globally. The complexity and diversity of cancer-related datasets across different specialties pose challenges in refining precision medicine for oncology. Foundation models offer a promising solution.
View Article and Find Full Text PDFAnnu Rev Clin Psychol
January 2025
Behavioral Pharmacology Research Unit, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; email:
The opioid crisis, driven by illicitly manufactured fentanyl, presents significant challenges in treating opioid use disorder (OUD) and opioid withdrawal syndrome. Fentanyl is uniquely lethal due to its rapid onset and respiratory depressant effects, driving the surge in overdose deaths. This review examines the limitations of traditional diagnostic criteria like those of the , Fifth Edition, Text Revision (DSM-5-TR) and explores the potential of dimensional models such as the Hierarchical Taxonomy of Psychopathology (HiTOP) for a more nuanced understanding of OUD.
View Article and Find Full Text PDFAm J Respir Crit Care Med
January 2025
University of Minnesota, Medicine, Minneapolis, Minnesota, United States.
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