Production of bowel sounds, established in the 1900s, has limited application in existing patient-care regimes and diagnostic modalities. We review the physiology of bowel sound production, the developments in recording technologies and the clinical application in various scenarios, to understand the potential of a bowel sound recording and analysis device—the phonoenterogram in future gastroenterological practice. Bowel sound production depends on but is not entirely limited to the type of food consumed, amount of air ingested and the type of intestinal contractions. Recording technologies for extraction and analysis of these include the wavelet-based filtering, autoregressive moving average model, multivariate empirical mode decompression, radial basis function network, two-dimensional positional mapping, neural network model and acoustic biosensor technique. Prior studies evaluate the application of bowel sounds in conditions such as intestinal obstruction, acute appendicitis, large bowel disorders such as inflammatory bowel disease and bowel polyps, ascites, post-operative ileus, sepsis, irritable bowel syndrome, diabetes mellitus, neurodegenerative disorders such as Parkinson’s disease and neonatal conditions such as hypertrophic pyloric stenosis. Recording and analysis of bowel sounds using artificial intelligence is crucial for creating an accessible, inexpensive and safe device with a broad range of clinical applications. Microwave-based digital phonoenterography has huge potential for impacting GI practice and patient care.

The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive tools that provide us with insight into daily physiology and aid in understanding pathology are within our grasp. Currently, our standards for estimating vital pressures, including continuous BP measurements, pulmonary capillary wedge pressures, and hepatic portal gradients, involve the use of invasive modalities. As an emerging field in medical technology, artificial intelligence (AI) has been incorporated into analyzing and predicting patterns of physiologic pressures. AI has been used to construct models that have clinical applicability both in hospital settings and at-home settings for ease of use for patients. Studies applying AI to each of these compartmental pressures were searched and shortlisted for thorough assessment and review. There are several AI-based innovations in noninvasive blood pressure estimation based on imaging, auscultation, oscillometry and wearable technology employing biosignals. The purpose of this review is to provide an in-depth assessment of the involved physiologies, prevailing methodologies and emerging technologies incorporating AI in clinical practice for each type of compartmental pressure measurement. We also bring to the forefront AI-based noninvasive estimation techniques for physiologic pressure based on microwave systems that have promising potential for clinical practice.

Viral hepatitis B is infamous for being contracted in young adulthood and adolescence, as high-risk behaviors like unprotected sexual intercourse and intravenous drug abuse are common. Most infections caused by the hepatitis B virus (HBV) are cleared without any long-term sequelae, but some may persist and cause chronic hepatitis B (CHB). This chronicity may produce a state of prolonged inflammation and significantly increase the risk of developing colorectal adenomas (CRA) and colorectal carcinomas (CRC). The aim of this review is to deep-dive into the mechanisms by which CHB may predispose a patient to develop CRA and, more grimly, CRC. It also focuses on studying the influence of CHB on colorectal cancer liver metastases (CRLM). We conducted a comprehensive literature search using databases like PubMed and Google Scholar, focusing on studies that investigate the role of HBV in colorectal carcinogenesis and CRLM rates in patients suffering from CHB. Chronic inflammation, viral protein interactions with tumor suppressor genes, alteration of cellular pathways such as wingless-related integration site (Wnt) signaling, and extrahepatic accumulation of hepatitis B surface antigen (HBsAg) were the key mechanisms identified. Quite peculiarly, CHB, which is thought to increase the risk for CRA, seemed to protect against CRLM probably due to its sclerosing effect on the liver parenchyma and due to certain immune-mediated mechanisms that suppress tumor growth. Nonetheless, high viral count or the presence of hepatitis B envelope antigen (HBeAg) was found to increase the risk for CRLM, potentially due to increased angiogenesis in the liver. These findings provide convincing evidence that enhanced colonoscopic screening and stronger management protocols for patients suffering from it have the potential to reduce the risk of developing CRC and CRLM.