Filipa Ferraz

Gaming in Dyscalculia: A Review on disMAT

Dyscalculia is a particular learning disability that affects around 6% of the world population. However, dyscalculics are not brainless; they fight to learn mathematics, notwithstanding nurturing an acceptable education environment at home and school. Indeed, dyscalculic children fall behind early in primary school, and may develop anxiety or a strong dislike of mathematics. When reach adult life are still paid less than ordinary people and have difficulties on handling their ordinary finances. Therefore, this work is about a game; disMAT, which is an app whose purpose entails to appeal children to train their mathematical skills. disMAT involves planning by choosing strategies for change as kids move through the game. Unlike a whole-class mathematics activity, a game may support one’s child’s individual needs. Undeniably, it must be challenging, have rules and structure, include a clear ending point, and focus on specific abilities.

A brief look into dyscalculia and supportive tools

Mathematics has always been a crucial matter to the human being since theirs existence. Therefore, it is across their development that its importance and complexity becomes noticeable. Either counting cookies or telling the hours, for someone with dyscalculia, these simple tasks become difficult to perform. Even if they fail developing these issues, it is not because they do not have the capacity to evolve their knowledge, but because they have a dysfunction appealing to be diagnosed, followed and treated. Consequently, diagnosis tests and therapeutic tasks will be implemented and the informatics version of it can increase potentially the success and precision of the results.

A Deep Learning Approach to Case Based Reasoning to the Evaluation and Diagnosis of Cervical Carcinoma

Deep Learning (DL) is a new area of Machine Learning research introduced with the objective of moving Machine Learning closer to one of its original goals, i.e., Artificial Intelligence (AI). DL breaks down tasks in ways that makes all kinds of machine assists seem possible, even likely. Better preventive healthcare, even better recommendations, are all here today or on the horizon. However, keeping up the pace of progress will require confronting currently AI’s serious limitations. The last but not the least, Cervical Carcinoma is actuality a critical public health problem. Although patients have a longer survival rate due to early diagnosis and more effective treatment, this disease is still the leading cause of cancer death among women. Therefore, the main objective of this article is to present a DL approach to Case Based Reasoning in order to evaluate and diagnose Cervical Carcinoma using Magnetic Resonance Imaging. It will be grounded on a dynamic virtual world of complex and interactive entities that compete against one another in which its aptitude is judged by a single criterion, the Quality of Information they carry and the system’s Degree of Confidence on such a measure, under a fixed symbolic structure.

A Case Base Approach to Cardiovascular Diseases using Chest X-ray Image Analysis

Cardio Vascular Disease (CVD) also known as heart and circulatory disease comprises all the illnesses of the heart and the circulatory system, namely coronary heart disease, angina, heart attack, congenital heart disease or stroke. CVDs are, nowadays, one of the main causes of death. Indeed, this fact reveals the centrality of prevention and how important is to be aware on these kind of situations. Thus, this work will focus on the development of a decision support system to help to prevent these events from happening, centred on a formal framework based on Mathematical Logic and Logic Programming for Knowledge Representation and Reasoning, complemented with a Case Based Reasoning approach to computing that caters to the handling of incomplete, unknown or even self-contradictory information or knowledge.

Diagnosis of Alzheimer Disease Through an Artificial Neural Network Based System

Alzheimer’s Disease (AD) is referred to as one of the most common causes of dementia, which in itself justifies the interest and investment that is made in order to find new biomarkers to identify the disease in its early stages. Indeed, focusing on the hippocampus as a marker for AD, it would be object of analyse different methods of volume measurement and hippocampus segmentation. On the other hand, the computational framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a computational framework base on Artificial Neural Networks that grip on incomplete, unknown, and even self-contradictory information or knowledge.

A Deep Learning Line to Assess Patient’s Lung Cancer Stages

Our goal is to pursue a vision of developing and maintaining a comprehensive and integrated computer model to help physicians plan the most appropriate treatment and anticipate a patient’s prospects for the extent of cancer. For example, cancer can be treated at an early stage by surgery or radiation, while chemotherapy may be the care for more advanced stages. In fact, early detection of this type of cancer facilitates its treatment and may rise the patients’ prospect of a continued existence. Thus, a formal view of an intelligent system for performing cancer feature extraction and analysis in order to establish the bases that will help physicians plan treatment and predict patient’s prognosis is presented. It is based on the Logic Programming Language and draws a line between Deep Learning and Knowledge Representation and Reasoning, and is supported by a Case Based attitude to computing. In fact, despite the fact that each patient’s condition is different, treating cancer at the same stage is often similar.

A Case-Based Reasoning Approach to GBM Evolution

GlioBastoma Multiforme (GBM) is an aggressive primary brain tumor characterized by a heterogeneous cell population that is genetically unstable and resistant to chemotherapy. Indeed, despite advances in medicine, patients diagnosed with GBM have a median survival of just one year. Magnetic Resonance Imaging (MRI) is the most widely used imaging technique for determining the location and size of brain tumors. Indisputably, this technique plays a major role in the diagnosis, treatment planning, and prognosis of GBM. Therefore, this study proposes a new Case Based Reasoning approach to problem solving that attempts to predict a patient’s GBM volume after five months of treatment based on features extracted from MR images and patient attributes such as age, gender, and type of treatment.

A Deep-Big Data Approach to Health Care in the AI Age

The intersection of these two trends is what we call The Issue and it is helping businesses in every industry to become more efficient and productive. One’s aim is to have an insight into the development and maintenance of comprehensive and integrated health information systems that enable sound policy and effective health system management in order to improve health and health care. Undeniably, different sorts of technologies have been developed, each with their own advantages and disadvantages, which will be sorted out by attending at the impact that Artificial Intelligence and Decision Support Systems have to everyone in the healthcare sector engaged to quality-of-care, i.e., making sure that doctors, nurses, and staff have the training and tools they need to do their jobs.

Collaborative Process Mapping to Improve Work Instructions and Standardized Work

Nowadays, companies are searching for models that are able to increase their performance, efficiency and competitiveness. Therefore, it is crucial to identify the current company status and its needs, adopting a suitable model for this. Many times, the success key consists in the adoption of tailor-made models developed by each organization. The company under study has developed a process mapping tool, called Value Stream Design in Indirect Areas (VSDiA) that has been used to map and improve its business processes, in this case, applied to Work Instructions and Standard Work creation. The adoption of this model has allowed the identification of weaknesses, strengths and improvement opportunities in the abovementioned processes, through a collaborative process team work. Furthermore, this tool has provided an overview about the whole process by all involved, as well as, increased transparency and accuracy of the current process and a vision for the future process.

Chest X-Ray Image Analysis

Most cardiovascular diseases can be prevented by addressing behavioral risk factors such as tobacco use, unhealthy diet and obesity, physical inactivity and harmful use of alcohol using strategies of the entire population. People with cardiovascular disease or high cardiovascular risk (due to the presence of one or more risk factors, such as hypertension, diabetes, hyperlipidemia or already established disease) need early detection and management using counseling and medication as appropriate. Now a leading cause of death. In fact, it reveals the centrality of prevention and how important it is to be aware of these situations. Thus, this paper will focus on the development of a decision support system to prevent these events to happen, centered on a structure based on Logic Programming for Representation and Knowledge Reasoning, complemented with a case-based approach to computation.