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Unlabelled: Prophylactic respiratory support for patients after extubation is effective in improving their outcomes and prognosis. However, the optimal post-extubation respiratory support for different populations and disease types of mechanically ventilated patients remains controversial, and there is a lack of detailed, multidisciplinary, evidence-based recommendations for clinical application.

Methods And Analysis: This protocol strictly follows the development process outlined in the WHO Handbook for Guideline Development and Guidelines 2.

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Background: Frailty is a complex clinical state that is associated with poorer health outcomes and increased dementia risk in older adults. It is routinely measured using the Frailty Index, which is a proportional score based on the number of 'deficits' that an individual has. Whilst such measures are useful for risk assessment, the aggregation of highly heterogeneous deficit profiles in genetic studies may obscure important insights into the underlying biology of frailty.

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Background: Plasma protein has gained prominence in the non-invasive predicting of lung cancer. We utilised Zeolite Zotero NaY-based plasma proteomics to investigate its potential for multiple event predicting, including lung cancer diagnosis (task #1), lymph node metastasis detection (task #2) and tumour‒node‒metastasis (TNM) staging (task #3).

Methods: A total of 4703 plasma proteins were quantified from 241 participants based on a prospective cohort of 2757 participants.

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Background: A 69-year-old retired businessman, born in 1954, with 12 years of education, had been participating in cognitive enhancement sessions for the past 5 years. His medical history included two ischemic strokes, left hemiplegia, as well as disturbances in the left visual field. This study aimed to examine the individual's cognitive performance over the course of these 5 years, including the COVID-19 pandemic period.

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The delivery of accurate diagnoses is crucial in healthcare and represents the gateway to appropriate and timely treatment. Although recent large language models (LLMs) have demonstrated impressive capabilities in few-shot or zero-shot learning, their effectiveness in clinical diagnosis remains unproven. Here we present MedFound, a generalist medical language model with 176 billion parameters, pre-trained on a large-scale corpus derived from diverse medical text and real-world clinical records.

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