Human-machine interactions with clinical phrase prediction system, aligning with Zipf's least effort principle?

The essence of language and its evolutionary determinants have long been research subjects with multifaceted explorations. This work reports on a large-scale observational study focused on the language use of clinicians interacting with a phrase prediction system in a clinical setting. By adopting principles of adaptation to evolutionary selection pressure, we attempt to identify the major determinants of language emergence specific to this context.

Prompt Engineering Paradigms for Medical Applications: Scoping Review.

Background: Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to its specialized terminology and language technicity. Clinical natural language processing applications must navigate complex language and ensure privacy compliance.

[Dolodoc: a virtual pain management coach].

Dolodoc is a mobile application aimed at improving autonomy and quality of life for individuals living with chronic pain. Designed as a virtual coach, it offers counseling according to 7 important dimensions of quality of life. Activities, pain and fulfillment of the 7 dimensions of quality of life can be recorded in the application.

A Novel Method and Python Library for ECG Signal Quality Assessment.

Electrocardiogram (ECG) is one of the reference cardiovascular diagnostic exams. However, the ECG signal is very prone to being distorted through different sources of artifacts that can later interfere with the diagnostic. For this reason, signal quality assessment (SQA) methods that identify corrupted signals are critical to improve the robustness of automatic ECG diagnostic methods.