Artificial intelligence to improve rehabilitation care for children with developmental conditions: Some ethical considerations.

This commentary is on the original article by Greve et al. on pages 100‐106 of this issue.

Automated recognition of functioning, activity and participation in COVID-19 from electronic patient records by natural language processing: a proof- of- concept.

Purpose: To address the feasibility, reliability and internal validity of natural language processing (NLP) for automated functional assessment of hospitalised COVID-19 patients in key International Classification of Functioning, Disability and Health (ICF) categories and levels from unstructured text in electronic health records (EHR) from a large teaching hospital.

Materials And Methods: Eight human annotators assigned four ICF categories to relevant sentences: Emotional functions, Exercise tolerance, Walking and Moving, Work and Employment and their ICF levels (Functional Ambulation Categories for Walking and Moving, metabolic equivalents for Exercise tolerance). A linguistic neural network-based model was trained on 80% of the annotated sentences; inter-annotator agreement (IAA, Cohen's kappa), a weighted score of precision and recall (F1) and RMSE for level detection were assessed for the remaining 20%.

How Concrete Do We Get Telling Stories?

Will reading different stories about the same event in the world result in a similar image of the world? Will reading the same story by different people result in a similar proxy for experiencing the story? The answer to both questions is no because language is abstract by definition and relies on our episodic experience to turn a story into a more concrete mental movie. Since our episodic knowledge differs, also the mental movie will be different. Language leaves out details, and this becomes specifically clear when building machines that read texts to represent events and to establish event relations across mentions, such as co-reference, causality, subevents, scripts, timelines, and storylines.

First Report of Neofabraea alba Causing Fruit Spot on Olive in North America.

Olive (Olea europaea) is a widely planted evergreen tree primarily grown for its oil, fruit for pickling, and landscape appeal in Mediterranean and temperate climates. California produces most of the olives grown in the United States; its industry was valued at $53 million in 2011 (4). In 2005 and 2008, fruit spotting occurred on coratina and picholine cultivars in two commercial orchards in Sonoma County.

Olive Twig and Branch Dieback: Etiology, Incidence, and Distribution in California.

Eighteen different fungal species were isolated from symptomatic wood of olive trees (Olea europaea) affected by twig and branch dieback in California and identified by means of morphological characters and multigene sequence analyses of the internal transcribed spacer (ITS) region (ITS1-5.8S-ITS2), a partial sequence of the β-tubulin gene, and part of the translation elongation factor 1-α gene (EF1-α). These species included Diaporthe viticola, Diatrype oregonensis, Diatrype stigma, Diplodia mutila, Dothiorella iberica, Lasiodiplodia theobromae, Phaeomoniella chlamydospora, Phomopsis sp.