AIMC Topic: Automation

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Are ChatGPT and large language models "the answer" to bringing us closer to systematic review automation?

Systematic reviews
In this commentary, we discuss ChatGPT and our perspectives on its utility to systematic reviews (SRs) through the appropriateness and applicability of its responses to SR related prompts. The advancement of artificial intelligence (AI)-assisted tech...

Parsable Clinical Trial Eligibility Criteria Representation Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Successful clinical trials offer better treatments to current or future patients and advance scientific research. Clinical trials define the target population using specific eligibility criteria to ensure an optimal enrollment sample. Clinical trial ...

Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact.

AMIA ... Annual Symposium proceedings. AMIA Symposium
A significant proportion of clinical physiologic monitoring alarms are false. This often leads to alarm fatigue in clinical personnel, inevitably compromising patient safety. To combat this issue, researchers have attempted to build Machine Learning ...

Mine local homogeneous representation by interaction information clustering with unsupervised learning in histopathology images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The success of data-driven deep learning for histopathology images often depends on high-quality training sets and fine-grained annotations. However, as tumors are heterogeneous and annotations are expensive, unsupervised le...

Novel AI-based HRV analysis (NAIHA) in healthcare automation and related applications.

Journal of electrocardiology
BACKGROUND: Heart rate variability (HRV) analysis computed on R-R interval series of ECG records with heavy burden of ectopic beats or non-sinus rhythm can significantly distort HRV parameters and hence clinically ineligible for HRV analysis. Yet, ex...

Artificial intelligence in molecular de novo design: Integration with experiment.

Current opinion in structural biology
In this mini review, we capture the latest progress of applying artificial intelligence (AI) techniques based on deep learning architectures to molecular de novo design with a focus on integration with experimental validation. We will cover the progr...

Dense reinforcement learning for safety validation of autonomous vehicles.

Nature
One critical bottleneck that impedes the development and deployment of autonomous vehicles is the prohibitively high economic and time costs required to validate their safety in a naturalistic driving environment, owing to the rarity of safety-critic...

A machine learning based approach for quantitative evaluation of cell migration in Transwell assays based on deformation characteristics.

The Analyst
Many pathological and physiological processes, including embryonic development, immune response and cancer metastasis, involve studies on cell migration, and especially detection methods, for which it is difficult to satisfy the requirements for rapi...

Effects of ultrasound with an automatic vessel detection system using artificial intelligence on the selection of puncture points among ultrasound beginner clinical nurses.

The journal of vascular access
BACKGROUND: Ultrasound guidance increases the success rate of peripheral intravenous catheter placement. However, the longer time required to obtain ultrasound-guided access poses difficulties for ultrasound beginners. Notably, interpretation of ultr...

Multi-agent medical image segmentation: A survey.

Computer methods and programs in biomedicine
During the last decades, the healthcare area has increasingly relied on medical imaging for the diagnosis of a growing number of pathologies. The different types of medical images are mostly manually processed by human radiologists for diseases detec...