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Archives of Gastroenterology Research
ISSN: 2692-5427
Volume 5, Issue 1, p1-12
Articles published in this issue are Open Access and licensed under Creative Commons Attribution License (CC BY NC) where the readers can reuse, download, distribute the article in whole or part by mentioning proper credits to the authors.
Optical Insights into Fibrotic Livers: Applications of Near-Infrared Spectroscopy and Machine Learning
Liver fibrosis staging is critical for patient selection and management prior to transplantation, but biopsy is invasive and serum biomarkers lack accuracy. Near-infrared spectroscopy (NIRS) is an emerging non-invasive technology that can detect liver fibrosis via changes in tissue composition. Machine learning (ML) enables analysis of NIRS data for diagnostic modeling.
Arch Gastroenterol Res, 2024, Volume 5, Issue 1, p1-10 | DOI: 10.33696/Gastroenterology.5.048Colonic Granular Cell Tumor
A 42-year-old asymptomatic woman presented for routine health checkup. Abdominal examination was unremarkable. The laboratory tests were normal. The chest radiograph, upper gastrointestinal endoscopy and abdominal computed tomography showed no abnormal findings. A colonoscopy was performed. A hepatic flexure polypoid mass (8 × 8 mm in diameter), covered with normal-appearing mucosa, was identified (Figure 1A).
Arch Gastroenterol Res, 2024, Volume 5, Issue 1, p11-12 | DOI: 10.33696/Gastroenterology.5.049Sentinel Lymph Node Biopsy after Neoadjuvant Chemotherapy for Breast Cancer
Breast cancer is the second most common cancer worldwide, affecting nearly one in eight women. Accurate cancer staging is essential for determining the patient’s prognosis and for choosing the appropriate treatment.
Machine Learning for Healthcare: Emerging Challenges and Opportunities in Disease Diagnosis
Diagnosis is a process that identifies, explains, or establishes the individual’s disease from its symptoms and signs. Early and precise diagnosis is crucial since it influences the efficacy of treatment and avoids longterm complications for the infected person. Further, in the case of infectious diseases, undiagnosed patients can transmit the disease to a healthy population unknowingly. Besides, most of the diseases evolve with the time that significantly affects the clinical outcomes.
Endoscopic Ultrasound-Guided Liver Biopsy, Is It Ready for Prime Time?
Liver biopsy continues to be the gold-standard with regards to diagnosis and staging of the majority of liver diseases. Serologic markers certainly have helped in diagnosing various autoimmune and viral-related liver diseases. Furthermore, laboratory testing and imaging studies such as liver elastography have allowed us to non-invasively assess fibrosis. Unfortunately, there are shortcomings with these forms of testing. False positives or laboratory errors will lead to misleading diagnoses. Situations can also arise during which there are diagnostic dilemmas, such as an obese patient with positive autoimmune serology and elevated liver chemistries.
Artificial Intelligence and Machine Learning in Cancer Care: Current Applications and Future Perspectives
Cancer is the second most common cause of death worldwide, accounting for an estimated 9.6 million deaths in the year 2018, a number that is expected to grow to more than 13 million by 2030. In the past decade, we have witnessed unprecedented scientific advancement in the understanding of cancer etiology, prevention, diagnosis and development of new therapeutic strategies.
Endoscopic Ultrasound-Guided Liver Biopsy; the Pathologist’s Perspective
In this study, the safety and efficacy of liver biopsies performed by endoscopic ultrasound (EUS-LB) were compared with those performed via the traditional percutaneous route at our Medical Center between January 2018 and August 2019.
EMG Signal Processing for Hand Motion Pattern Recognition Using Machine Learning Algorithms
Stroke is a major cause of death and disability in the world. There were approximately 25.7 million stroke survivors and 6.5 million deaths from stroke [1]. Stroke can result in arm disability and reduce daily life activity via weak arm muscle activity [2]. Studies have been performed to discover therapeutic and assistive approaches to compensate for disabilities and restore functions.
A Protocol for the Generation of Treatment-naïve Biopsy-derived Diffuse Intrinsic Pontine Glioma and Diffuse Midline Glioma Models
Diffuse intrinsic pontine glioma (DIPG) is an aggressive brain tumor that arises in the ventral pons during middle childhood.
Comparing Contrast Agent Enhancement: The Value of Artificial Intelligence/Machine Learning
Gadolinium-based contrast agents (GBCAs) work by shortening the T1, T2, and T2* relaxation time constants of adjacent water protons in tissues.
A Machine Learning Study of 534,023 Medicare Beneficiaries with COVID-19: Implications for Personalized Risk Prediction for People Over 65
The global outbreak of COVID-19 has resulted in over 378 million infections and worldwide deaths have surpassed 5.6 million. In the United States, there have been over 75 million confirmed cases and over 886,000 deaths as of February 1, 2022.
Optical Insights into Fibrotic Livers: Applications of Near-Infrared Spectroscopy and Machine Learning
Liver fibrosis staging is critical for patient selection and management prior to transplantation, but biopsy is invasive and serum biomarkers lack accuracy. Near-infrared spectroscopy (NIRS) is an emerging non-invasive technology that can detect liver fibrosis via changes in tissue composition. Machine learning (ML) enables analysis of NIRS data for diagnostic modeling.
Colonic Granular Cell Tumor
A 42-year-old asymptomatic woman presented for routine health checkup. Abdominal examination was unremarkable. The laboratory tests were normal. The chest radiograph, upper gastrointestinal endoscopy and abdominal computed tomography showed no abnormal findings. A colonoscopy was performed. A hepatic flexure polypoid mass (8 × 8 mm in diameter), covered with normal-appearing mucosa, was identified (Figure 1A).
Role of a Training Simulator for Kidney Biopsy and Tumor Removal Procedures in Complex Positioning Scenarios: The Key Challenges
Preventable medical errors and iatrogenic injuries remain significant contributors to mortality and morbidity, emphasizing the need for effective clinical training methodologies. Traditional teaching methods often inadequately prepare physicians for mastering procedural skills. Surgical procedures like nephrectomy for kidney tumor removal require intricate understanding of renal anatomy and meticulous technique. Close coordination among the specialists remains crucial to ensure optimal patient outcomes.
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