Portuguese version of the Literacy Independent Cognitive Assessment (LICA) instrument in the evaluation of individuals aged 50 years or older with Itabaianinha syndrome.

Objectives: Individuals with congenital isolated growth hormone deficiency (IGHD) in Northeastern Brazil have a normal lifespan with a prolonged healthspan. We hypothesize that their increased healthspan is accompanied by a reduced cognitive decline during aging. We have recently shown that these individuals have a similar total cognitive function and better attention and executive function than controls.

Reducing Training Data Using Pre-Trained Foundation Models: A Case Study on Traffic Sign Segmentation Using the Segment Anything Model.

The utilization of robust, pre-trained foundation models enables simple adaptation to specific ongoing tasks. In particular, the recently developed Segment Anything Model (SAM) has demonstrated impressive results in the context of semantic segmentation. Recognizing that data collection is generally time-consuming and costly, this research aims to determine whether the use of these foundation models can reduce the need for training data.

Prediction rigidities for data-driven chemistry.

The widespread application of machine learning (ML) to the chemical sciences is making it very important to understand how the ML models learn to correlate chemical structures with their properties, and what can be done to improve the training efficiency whilst guaranteeing interpretability and transferability. In this work, we demonstrate the wide utility of prediction rigidities, a family of metrics derived from the loss function, in understanding the robustness of ML model predictions. We show that the prediction rigidities allow the assessment of the model not only at the global level, but also on the local or the component-wise level at which the intermediate ( atomic, body-ordered, or range-separated) predictions are made.