Publications by authors named "Keerthy Gopalakrishnan"

Accurate diagnosis of gastrointestinal (GI) diseases typically requires invasive procedures or imaging studies that pose the risk of various post-procedural complications or involve radiation exposure. Bowel sounds (BSs), though typically described during a GI-focused physical exam, are highly inaccurate and variable, with low clinical value in diagnosis. Interpretation of the acoustic characteristics of BSs, i.

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Accurate analysis of medical videos remains a major challenge in deep learning (DL) due to the need for effective spatiotemporal feature mapping that captures both spatial detail and temporal dynamics. Despite advances in DL, most existing models in medical AI focus on static images, overlooking critical temporal cues present in video data. To bridge this gap, a novel DL-based framework is proposed for spatiotemporal feature extraction from medical video sequences.

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Objective: Achalasia is an esophageal motility disorder associated with halting symptoms. There is conflicting evidence about the feasibility of peroral endoscopic myotomy (POEM) for achalasia among the elderly. In this meta-analysis, we sought to evaluate POEM's therapeutic safety and efficacy among elderly patients with achalasia.

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Background And Aims: Patients with inflammatory bowel disease (IBD) face increased risk of colorectal cancer (CRC). While the natural history of conventional dysplastic precursor lesions has been well-studied, the neoplastic potential of recently described nonconventional (NC) IBD-associated colonic mucosal lesions is unclear. We aimed to assess the incidence of antecedent NC lesions in patients with IBD who developed CRC.

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Background: Per-oral endoscopic myotomy (POEM) is an effective option for treating achalasia. Despite its high efficacy, a fraction of patients remain symptomatic after POEM, and the data on the optimal management of these patients is limited. Few studies have evaluated the effectiveness of repeat POEM after a failed POEM.

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Article Synopsis
  • Measurement of physiologic pressure is crucial for diagnosing and preventing health complications, utilizing various invasive and noninvasive tools in both clinical and home settings.
  • AI technologies are emerging in this field, helping to analyze and predict patterns of physiologic pressures, thus enhancing patient care.
  • The review explores different methodologies and innovations, particularly highlighting AI-based noninvasive techniques like microwave systems for estimating physiologic pressure and their potential in clinical applications.
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Respiratory disorders, being one of the leading causes of disability worldwide, account for constant evolution in management technologies, resulting in the incorporation of artificial intelligence (AI) in the recording and analysis of lung sounds to aid diagnosis in clinical pulmonology practice. Although lung sound auscultation is a common clinical practice, its use in diagnosis is limited due to its high variability and subjectivity. We review the origin of lung sounds, various auscultation and processing methods over the years and their clinical applications to understand the potential for a lung sound auscultation and analysis device.

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Article Synopsis
  • Bowel sounds, first studied in the 1900s, have limited use in current patient care, yet they hold promise for future diagnostic practices through advanced recording technologies like phonoenterograms.
  • The production of bowel sounds is influenced by factors such as diet, air intake, and intestinal contractions, and new technologies allow for sophisticated analysis of these sounds using methods like neural networks and acoustic biosensors.
  • Previous research indicates bowel sounds can help diagnose various gastrointestinal conditions, and incorporating AI into their analysis may lead to the development of an effective, affordable, and safe diagnostic device for broader clinical use.
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The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (εr) and conductivity (σ), can vary significantly between healthy and unhealthy tissue types at a given frequency.

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Morgellons disease (MD) is a rare dermatopathy characterized by nonspecific symptoms and the production of multicolored fibers and granular tissue from diffuse skin ulcerations which are described as being either pruritic or painful. The etiology of MD is currently unknown; previous studies have suggested both psychiatric and infectious causes, with increasing interest over the previous decade in elaborating a possible pathogenesis for the disease secondary to infection by Borrelia species. We report a middle-aged Caucasian female who developed symptoms of MD in the days following exposure to a tick bite after spending an afternoon hiking through a wooded area.

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