Publications by authors named "Gopal Kotecha"

The development and evaluation of novel treatment combinations is a key component of modern clinical research. The primary goals of factorial clinical trials of treatment combinations range from the estimation of intervention-specific effects, or the discovery of potential synergies, to the identification of combinations with the highest response probabilities. Most factorial studies use balanced or block randomization, with an equal number of patients assigned to each treatment combination, irrespective of the specific goals of the trial.

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Regulation is necessary to ensure the safety, efficacy and equitable impact of clinical artificial intelligence (AI). The number of applications of clinical AI is increasing, which, amplified by the need for adaptations to account for the heterogeneity of local health systems and inevitable data drift, creates a fundamental challenge for regulators. Our opinion is that, at scale, the incumbent model of centralized regulation of clinical AI will not ensure the safety, efficacy, and equity of implemented systems.

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Article Synopsis
  • Sharing data from control groups in similar clinical trials can improve efficiency in drug development.
  • There are both potential benefits, like increased data availability, and risks, such as privacy concerns related to data sharing.
  • The article explores these aspects to highlight how effective data-sharing plans can impact concurrent randomized trials.
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Background: Digital Imaging and Communications in Medicine (DICOM) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network.

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Chronic pain is a common, often disabling condition thought to involve a combination of peripheral and central neurobiological factors. However, the extent and nature of changes in the brain is poorly understood. We investigated brain network architecture using resting-state fMRI data in chronic back pain patients in the UK and Japan (41 patients, 56 controls), as well as open data from USA.

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