In the practical deployment of machine learning (ML) models, missing data represents a recurring challenge. Missing data is often addressed when training ML models. But missing data also needs to be addressed when deciding predictions and when explaining those predictions. Missing data represents an opportunity to partially specify the inputs of the prediction to be explained. This paper studies the computation of logic-based explanations in the presence of partially specified inputs. The paper shows that most of the algorithms proposed in recent years for computing logic-based explanations can be generalized for computing explanations given the partially specified inputs. One related result is that the complexity of computing logic-based explanations remains unchanged. A similar result is proved in the case of logic-based explainability subject to input constraints. Furthermore, the proposed solution for computing explanations given partially specified inputs is applied to classifiers obtained from well-known public datasets, thereby illustrating a number of novel explainability use cases.

In a recent article published in the journal Sensors, researchers perform a scoping review on the shared relationship between artificial intelligence (AI) and neuroscience, emphasizing their convergence and possible applications. The researchers extensively searched existing literature relevant to the objective of this review. As a result, the final dataset comprised 185 publications, 173 of which were from scientific databases, and the remaining 12 were hyperlink references from Google. Neuroscience principles have uplifted the AI field and vice versa. For example, neuroscience has helped researchers validate existing AI-based models.

There's been significant investment in companies creating artificial intelligence (AI) applications for health and health care over the last decade. But while there have been successes, notably in the area of medical imaging, the industry is known more for not yet living up to its potential -- think IBM Watson. The slow pace of AI adoption in health care stems from the fact that health AI sits on the border between two large industries, health care and tech. And like the border between two nations, there are significant differences on either side. During my career, I have spent time on each side.

Abstract: Meningitis is defined as inflammation of the meninges, in almost all cases identified by an abnormal number of white blood cells in the cerebrospinal fluid and specific clinical signs/symptoms. Onset may be acute or chronic, and clinical symptoms of acute disease develop over hours to days. This article reviews the epidemiology, pathophysiology, clinical manifestations, diagnosis, and management of acute meningitis, and provides a list of key points for primary care practitioners. Aseptic and bacterial meningitis vary significantly and are discussed separately. Abstract: Chronic meningitis is an inflammation of the meninges with subacute onset and persisting cerebrospinal fluid (CSF) abnormalities lasting for at least one month.

Unlike linear models and SVM (see Part 1), some machine learning models are really complex to learn from their mathematical formulation. Fortunately, they can be understood by following a step-by-step process they execute on a small dummy dataset. This way, you can uncover machine learning models under the hood without the "math bottleneck". You will learn three more models in this story after Part 1: K-Nearest Neighbors (KNN), Naive Bayes, and Decision Tree. KNN is a non-generalizing machine learning model since it simply "remembers" all of its train data.

An 11-year-old Star Wars fanatic who lost his left hand and both legs below the knee to meningitis has been given an R2D2-themed bionic hand. Kye Vincent, of Leighton Buzzard, Bedfordshire, was given days to live in April 2016 when he was struck down with the killer infection. The youngster, then eight, was placed into an induced coma and spent 38 weeks in hospital, where doctors were forced to remove his legs, his left hand and part of his right hand. But in the years since, Kye has made a remarkable recovery and has capped the end of a long journey with a £10,000 bionic arm. The prosthetic, called a Hero Arm, has been designed to look like the the droid R2-D2, an iconic character from the Star Wars franchise.

Enteroviruses are important drivers of global health, but few countries undertake enterovirus surveillance. Pons-Salort and Grassly used Japanese surveillance data to model the interplay between the ratio of susceptible and immune individuals, accounting for declining birth and death rates, incomplete surveillance, and seasonality of infection (see the Perspective by Nikolay and Cauchemez). Enteroviruses have highly predictable yet highly nonlinear dynamics. The model also reveals signatures of increased pathogenicity and of antigenic change and transmissibility. Science, this issue p. 800; see also p. 755 Human enteroviruses are a major cause of neurological and other diseases.

Her remains were mummified over 2,000 years ago, but a 3D scanning system has shed new light on the life of a five year old girl from Egypt. Scientists have used 3D scanning to create an exact digital copy of the mummy, revealing how it looks on the outside and inside. The scans revealed that the mummified remains belonged to a girl aged between 4.5 and six, who likely died from dysentery or meningitis. The mummified Egyptian child has been called Sherit, which is ancient Egyptian for'little one.' The mummy has been stored at the Rosicrucian Egyptian Museum in San Jose since 1930, although little is known about where it came from.

EXPERT SYSTEMS Computers as sages by Howard Rheingold Howard Rheingold is the author of Software Odyssey and co-author of Higher Creativity. Should you ever want to drill for oil, diagnose a disease or synthesize a new molecule, you can ask Prospector, MYCIN or Dendral for some sage advice. They are certified experts in their respective fields. They are also computer programs. We all depend on expert assistance-from doctors, attorneys, automobile mechanics, computer repairmen.

Instead they have commonly assigned structure to a domain using statistical techniques such as Bayes' Theorem