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Suri C, Pande B, Sahu T, Sahithi LS, Verma HK. Revolutionizing Gastrointestinal Disorder Management: Cutting-Edge Advances and Future Prospects. J Clin Med 2024; 13:3977. [PMID: 38999541 PMCID: PMC11242723 DOI: 10.3390/jcm13133977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Revised: 06/22/2024] [Accepted: 06/29/2024] [Indexed: 07/14/2024] Open
Abstract
In recent years, remarkable strides have been made in the management of gastrointestinal disorders, transforming the landscape of patient care and outcomes. This article explores the latest breakthroughs in the field, encompassing innovative diagnostic techniques, personalized treatment approaches, and novel therapeutic interventions. Additionally, this article emphasizes the use of precision medicine tailored to individual genetic and microbiome profiles, and the application of artificial intelligence in disease prediction and monitoring. This review highlights the dynamic progress in managing conditions such as inflammatory bowel disease, gastroesophageal reflux disease, irritable bowel syndrome, and gastrointestinal cancers. By delving into these advancements, we offer a glimpse into the promising future of gastroenterology, where multidisciplinary collaborations and cutting-edge technologies converge to provide more effective, patient-centric solutions for individuals grappling with gastrointestinal disorders.
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Affiliation(s)
- Chahat Suri
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, AB T6G 1Z2, Canada
- Lung Health and Immunity, Helmholtz Zentrum Munich, IngolstädterLandstraße 1, 85764 Oberschleißheim, 85764 Munich, Germany
| | - Babita Pande
- Department of Physiology, All India Institute of Medical Science, Raipur 492099, India
| | - Tarun Sahu
- Department of Physiology, All India Institute of Medical Science, Raipur 492099, India
| | | | - Henu Kumar Verma
- Lung Health and Immunity, Helmholtz Zentrum Munich, IngolstädterLandstraße 1, 85764 Oberschleißheim, 85764 Munich, Germany
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Chato L, Regentova E. Survey of Transfer Learning Approaches in the Machine Learning of Digital Health Sensing Data. J Pers Med 2023; 13:1703. [PMID: 38138930 PMCID: PMC10744730 DOI: 10.3390/jpm13121703] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 12/01/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
Machine learning and digital health sensing data have led to numerous research achievements aimed at improving digital health technology. However, using machine learning in digital health poses challenges related to data availability, such as incomplete, unstructured, and fragmented data, as well as issues related to data privacy, security, and data format standardization. Furthermore, there is a risk of bias and discrimination in machine learning models. Thus, developing an accurate prediction model from scratch can be an expensive and complicated task that often requires extensive experiments and complex computations. Transfer learning methods have emerged as a feasible solution to address these issues by transferring knowledge from a previously trained task to develop high-performance prediction models for a new task. This survey paper provides a comprehensive study of the effectiveness of transfer learning for digital health applications to enhance the accuracy and efficiency of diagnoses and prognoses, as well as to improve healthcare services. The first part of this survey paper presents and discusses the most common digital health sensing technologies as valuable data resources for machine learning applications, including transfer learning. The second part discusses the meaning of transfer learning, clarifying the categories and types of knowledge transfer. It also explains transfer learning methods and strategies, and their role in addressing the challenges in developing accurate machine learning models, specifically on digital health sensing data. These methods include feature extraction, fine-tuning, domain adaptation, multitask learning, federated learning, and few-/single-/zero-shot learning. This survey paper highlights the key features of each transfer learning method and strategy, and discusses the limitations and challenges of using transfer learning for digital health applications. Overall, this paper is a comprehensive survey of transfer learning methods on digital health sensing data which aims to inspire researchers to gain knowledge of transfer learning approaches and their applications in digital health, enhance the current transfer learning approaches in digital health, develop new transfer learning strategies to overcome the current limitations, and apply them to a variety of digital health technologies.
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Affiliation(s)
- Lina Chato
- Department of Electrical and Computer Engineering, University of Nevada, Las Vegas, NV 89154, USA;
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Fonseka LN, Woo BKP. Therapeutic role of psilocybin and 3,4-methylenedioxymethamphetamine in trauma: A literature review. World J Psychiatry 2023; 13:182-190. [PMID: 37303932 PMCID: PMC10251361 DOI: 10.5498/wjp.v13.i5.182] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/28/2023] [Accepted: 04/13/2023] [Indexed: 05/19/2023] Open
Abstract
With the Food and Drug Administration designation in 2017 of 3,4-methylenedioxymethamphetamine (MDMA) as a breakthrough therapy in post-traumatic stress disorder and psilocybin in treatment-resistant depression, psychedelic drugs have continued to garner the attention of researchers and clinicians for their promise of unmatched, rapid improvement in a multitude of psychiatric conditions. Classic psychedelic drugs including psilocybin, lysergic acid diethylamide, and ayahuasca, as well as non-classic drugs such as MDMA and ketamine, are currently being investigated for a potential therapeutic role in trauma, depressive disorders, and other psychopathologies. However, psilocybin and MDMA each have a functional profile well-suited for integration with psychotherapy. The present review focuses on psilocybin and MDMA in psychedelic-assisted therapy (PAT), as these studies compose most of the literature pool. In this review, we discuss the current and future uses of psychedelic drugs, with an emphasis on the role of MDMA and psilocybin in PAT in the setting of trauma and related comorbidities on the efficacy of psychedelic drugs across multiple psychiatric disorders. The article concludes with thoughts for future research, such as incorporating wearables and standardization of symptom scales, therapy styles, and assessment of adverse drug reactions.
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Affiliation(s)
- Lakshan N Fonseka
- Harvard South Shore-Psychiatry Residency Program, Veteran Affairs Boston Healthcare System, Brockton, MA 02301, United States
| | - Benjamin KP Woo
- Chinese American Health Promotion Laboratory, University of California, Los Angeles, Los Angeles, CA 90095, United States
- Department of Psychiatry and Biobehavioral Sciences, Olive View - University of California, Los Angeles Medical Center, Sylmar, CA 91342, United States
- Asian American Studies Center, University of California, Los Angeles, Los Angeles, CA 90095, United States
- Podiatric Medicine and Surgery, Western University of Health Sciences, Pomona, CA 91766, United States
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Messner EM, Sturm N, Terhorst Y, Sander LB, Schultchen D, Portenhauser A, Schmidbaur S, Stach M, Klaus J, Baumeister H, Walter BM. Mobile Apps for the Management of Gastrointestinal Diseases: Systematic Search and Evaluation Within App Stores. J Med Internet Res 2022; 24:e37497. [PMID: 36197717 PMCID: PMC9582913 DOI: 10.2196/37497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 05/30/2022] [Accepted: 07/29/2022] [Indexed: 11/29/2022] Open
Abstract
Background Gastrointestinal diseases are associated with substantial cost in health care. In times of the COVID-19 pandemic and further digitalization of gastrointestinal tract health care, mobile health apps could complement routine health care. Many gastrointestinal health care apps are already available in the app stores, but the quality, data protection, and reliability often remain unclear. Objective This systematic review aimed to evaluate the quality characteristics as well as the privacy and security measures of mobile health apps for the management of gastrointestinal diseases. Methods A web crawler systematically searched for mobile health apps with a focus on gastrointestinal diseases. The identified mobile health apps were evaluated using the Mobile Application Rating Scale (MARS). Furthermore, app characteristics, data protection, and security measures were collected. Classic user star rating was correlated with overall mobile health app quality. Results The overall quality of the mobile health apps (N=109) was moderate (mean 2.90, SD 0.52; on a scale ranging from 1 to 5). The quality of the subscales ranged from low (mean 1.89, SD 0.66) to good (mean 4.08, SD 0.57). The security of data transfer was ensured only by 11 (10.1%) mobile health apps. None of the mobile health apps had an evidence base. The user star rating did not correlate with the MARS overall score or with the individual subdimensions of the MARS (all P>.05). Conclusions Mobile health apps might have a positive impact on diagnosis, therapy, and patient guidance in gastroenterology in the future. We conclude that, to date, data security and proof of efficacy are not yet given in currently available mobile health apps.
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Affiliation(s)
- Eva-Maria Messner
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Ulm, Germany
| | - Niklas Sturm
- Department of Internal Medicine I, University Hospital Ulm, Ulm, Germany
| | - Yannik Terhorst
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Ulm, Germany.,Department of Research Methods, Institute of Psychology and Education, University of Ulm, Ulm, Germany
| | - Lasse B Sander
- Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, Albert-Ludwigs-University Freiburg, Freiburg at Breisgau, Germany
| | - Dana Schultchen
- Department of Clinical and Health Psychology, Institute of Psychology and Education, University of Ulm, Ulm, Germany
| | - Alexandra Portenhauser
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Ulm, Germany
| | - Simone Schmidbaur
- Department of Internal Medicine I, University Hospital Ulm, Ulm, Germany
| | - Michael Stach
- Institute of Databases and Information Systems, University of Ulm, Ulm, Germany
| | - Jochen Klaus
- Department of Internal Medicine I, University Hospital Ulm, Ulm, Germany
| | - Harald Baumeister
- Department of Clinical Psychology and Psychotherapy, Institute of Psychology and Education, University of Ulm, Ulm, Germany
| | - Benjamin M Walter
- Department of Internal Medicine I, University Hospital Ulm, Ulm, Germany
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Fonseka LN, Woo BKP. Wearables in Schizophrenia: Update on Current and Future Clinical Applications. JMIR Mhealth Uhealth 2022; 10:e35600. [PMID: 35389361 PMCID: PMC9030897 DOI: 10.2196/35600] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/07/2022] [Accepted: 03/22/2022] [Indexed: 01/08/2023] Open
Abstract
Schizophrenia affects 1% of the world population and is associated with a reduction in life expectancy of 20 years. The increasing prevalence of both consumer technology and clinical-grade wearable technology offers new metrics to guide clinical decision-making remotely and in real time. Herein, recent literature is reviewed to determine the potential utility of wearables in schizophrenia, including their utility in diagnosis, first-episode psychosis, and relapse prevention and their acceptability to patients. Several studies have further confirmed the validity of various devices in their ability to track sleep—an especially useful metric in schizophrenia, as sleep disturbances may be predictive of disease onset or the acute worsening of psychotic symptoms. Through machine learning, wearable-obtained heart rate and motor activity were used to differentiate between controls and patients with schizophrenia. Wearables can capture the autonomic dysregulation that has been detected when patients are actively experiencing paranoia, hallucinations, or delusions. Multiple platforms are currently being researched, such as Health Outcomes Through Positive Engagement and Self-Empowerment, Mobile Therapeutic Attention for Treatment-Resistant Schizophrenia, and Sleepsight, that may ultimately link patient data to clinicians. The future is bright for wearables in schizophrenia, as the recent literature exemplifies their potential to offer real-time insights to guide diagnosis and management.
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Affiliation(s)
- Lakshan N Fonseka
- Olive View-University of California Los Angeles Medical Center, Sylmar, CA, United States
| | - Benjamin K P Woo
- Olive View-University of California Los Angeles Medical Center, Sylmar, CA, United States
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Fonseka LN, Woo BK. Consumer Wearables and the Integration of New Objective Measures in Oncology: Patient and Provider Perspectives. JMIR Mhealth Uhealth 2021; 9:e28664. [PMID: 34264191 PMCID: PMC8323022 DOI: 10.2196/28664] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 04/12/2021] [Accepted: 06/11/2021] [Indexed: 12/15/2022] Open
Abstract
With one in five adults in the United States owning a smartwatch or fitness tracker, these devices are poised to impact all aspects of medicine by offering a more objective approach to replace self-reported data. Oncology has proved to be a prototypical example, and wearables offer immediate benefits to patients and oncologists with the ability to track symptoms and health metrics in real time. We aimed to review the recent literature on consumer-grade wearables and its current applications in cancer from the perspective of both the patient and the provider. The relevant studies suggested that these devices offer benefits, such as improved medication adherence and accuracy of symptom tracking over self-reported data, as well as insights that increase patient empowerment. Physical activity is consistently correlated with stronger patient outcomes, and a patient's real-time metrics were found to be capable of tracking medication side effects and toxicity. Studies have made associations between wearable data and telomere shortening, cardiovascular disease, alcohol consumption, sleep apnea, and other conditions. The objective data obtained by the wearable presents a more complete picture of an individual's health than the snapshot of a 15-minute office visit and a single set of vital signs. Real-time metrics can be translated into a digital phenotype that identifies risk factors specific to each patient, and shared risk factors across one's social network may uncover common environmental exposures detrimental to one's health. Wearable data and its upcoming integration with social media will be the foundation for the next generation of personalized medicine.
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Affiliation(s)
- Lakshan N Fonseka
- College of Osteopathic Medicine of the Pacific, Western University of Health Sciences, Pomona, CA, United States
| | - Benjamin Kp Woo
- Olive View-University of California, Los Angeles Medical Center, Sylmar, CA, United States
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