Publications by authors named "Anirudh Joshi"

Article Synopsis
  • Researchers created AI-based histologic assays to predict the likelihood of recurrence and progression in patients with high-risk non-muscle invasive bladder cancer after treatment with intravesical BCG.
  • They analyzed whole-slide images from bladder tumor resections and clinical data from multiple centers, successfully categorizing cases into high or low risk for various outcomes.
  • The validation cohort showed that high-risk patients had significantly worse survival outcomes, indicating that these AI assays provide crucial predictive information beyond traditional clinical factors.
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Pancreatic ductal adenocarcinoma (PDAC) has been left behind in the evolution of personalized medicine. Predictive markers of response to therapy are lacking in PDAC despite various histological and transcriptional classification schemes. We report an artificial intelligence (AI) approach to histologic feature examination that extracts a signature predictive of disease-specific survival (DSS) in patients with PDAC receiving adjuvant gemcitabine.

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Heart rate and through-body blood perfusion are vital measurements in all stages of patient care, be it predictive, in the clinical setting, or outpatient monitoring. Irregular, underachieving, or overperforming heart rate is the main precursor of most cardiovascular diseases that have severe long-term complications. In addition to heart rate, the shape of the pulse waveforms can indicate the heart's valve health and electrophysiology health.

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The current norm for measuring blood pressure (BP) at home is using an automated BP cuff based on oscillometry. Despite providing a viable and familiar method of tracking BP at home, oscillometric devices can be both cumbersome and inaccurate with the inconvenience of the hardware typically limiting measurements to once or twice per day. To address these limitations, a wrist-watch BP monitor was developed to measure BP through a simple maneuver: holding the watch against the sternum to detect micro-vibrations of the chest wall associated with the heartbeat.

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