Hybrid model for early identification post-Covid-19 sequelae.

Artificial Intelligence techniques based on Machine Learning algorithms, Neural Networks and Naïve Bayes can optimise the diagnostic process of the SARS-CoV-2 or Covid-19. The most significant help of these techniques is analysing data recorded by health professionals when treating patients with this disease. Health professionals' more specific focus is due to the reduction in the number of observable signs and symptoms, ranging from an acute respiratory condition to severe pneumonia, showing an efficient form of attribute engineering.

Identifying congenital generalized lipodystrophy using deep learning-DEEPLIPO.

Congenital Generalized Lipodystrophy (CGL) is a rare autosomal recessive disease characterized by near complete absence of functional adipose tissue from birth. CGL diagnosis can be based on clinical data including acromegaloid features, acanthosis nigricans, reduction of total body fat, muscular hypertrophy, and protrusion of the umbilical scar. The identification and knowledge of CGL by the health care professionals is crucial once it is associated with severe and precocious cardiometabolic complications and poor outcome.

Applications of Technological Solutions in Primary Ways of Preventing Transmission of Respiratory Infectious Diseases-A Systematic Literature Review.

With the growing concern about the spread of new respiratory infectious diseases, several studies involving the application of technology in the prevention of these diseases have been carried out. Among these studies, it is worth highlighting the importance of those focused on the primary forms of prevention, such as social distancing, mask usage, quarantine, among others. This importance arises because, from the emergence of a new disease to the production of immunizers, preventive actions must be taken to reduce contamination and fatalities rates.

A Protocol for the Diagnosis of Autism Spectrum Disorder Structured in Machine Learning and Verbal Decision Analysis.

Autism Spectrum Disorder is a mental disorder that afflicts millions of people worldwide. It is estimated that one in 160 children has traces of autism, with five times the higher prevalence in boys. The protocols for detecting symptoms are diverse.

Computer-assisted Parkinson's disease diagnosis using fuzzy optimum- path forest and Restricted Boltzmann Machines.

Parkinson's disease (PD) is a progressive neurodegenerative illness associated with motor skill disorders, affecting thousands of people, mainly elderly, worldwide. Since its symptoms are not clear and commonly confused with other diseases, providing early diagnosis is a challenging task for traditional methods. In this context, computer-aided assistance is an alternative method for a fast and automatic diagnosis, accelerating the treatment and alleviating an excessive effort from professionals.

CovidGAN: Data Augmentation Using Auxiliary Classifier GAN for Improved Covid-19 Detection.

Coronavirus (COVID-19) is a viral disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect on the global economy and health. A positive chest X-ray of infected patients is a crucial step in the battle against COVID-19.

A Multi-Objective Demand Response Optimization Model for Scheduling Loads in a Home Energy Management System.

Demand Response (DR) aims to motivate end consumers to change their energy consumption patterns in response to changes in electricity prices or when the reliability of the electrical power system (EPS) is compromised. Most of the proposals found in the literature only aim at reducing the cost for end consumers. However, this article proposes a home energy management system (HEMS) that aims to schedule the use of each home appliance based on the price of electricity in real-time (RTP) and on the consumer satisfaction/comfort level in order to guarantee the stability and the safety of the EPS.

Energy Efficient Management of Pipelines in Buildings Using Linear Wireless Sensor Networks.

The efficient and safe management of air conditioner (AC), Piped Natural Gas (PNG) and water pipelines in large buildings is a major challenge for the safety of these buildings. In recent years, Linear Wireless Sensor Networks (LWSN) are being used extensively for monitoring of long natural gas, water, and oil pipelines. LWSNs can also be used for efficient and safe management of AC, PNG and water pipelines in large buildings.

Reducing the Schizophrenia Stigma: A New Approach Based on Augmented Reality.

Schizophrenia is a chronic mental disease that usually manifests psychotic symptoms and affects an individual's functionality. The stigma related to this disease is a serious obstacle for an adequate approach to its treatment. Stigma can, for example, delay the start of treatment, and it creates difficulties in interpersonal and professional relationships.

Novel Virtual Environment for Alternative Treatment of Children with Cerebral Palsy.

Cerebral palsy is a severe condition usually caused by decreased brain oxygenation during pregnancy, at birth or soon after birth. Conventional treatments for cerebral palsy are often tiresome and expensive, leading patients to quit treatment. In this paper, we describe a virtual environment for patients to engage in a playful therapeutic game for neuropsychomotor rehabilitation, based on the experience of the occupational therapy program of the Nucleus for Integrated Medical Assistance (NAMI) at the University of Fortaleza, Brazil.

Handling diagnosis of schizophrenia by a hybrid method.

Psychotics disorders, most commonly known as schizophrenia, have incapacitated professionals in different sectors of activities. Those disorders have caused damage in a microlevel to the individual and his/her family and in a macrolevel to the economic and production system of the country. The lack of early and sometimes very late diagnosis has provided reactive measures, when the professional is already showing psychological signs of incapacity to work.

Toward an application to psychological disorders diagnosis.

Psychological disorders have kept away and incapacitated professionals in different sectors of activities. The most serious problems may be associated with various types of pathologies; however, it appears, more often, as psychotic disorders, mood disorders, anxiety disorders, antisocial personality, multiple personality and addiction, causing a micro level damage to the individual and his/her family and in a macro level to the production system and the country welfare. The lack of early diagnosis has provided reactive measures, and sometimes very late, when the professional is already showing psychological signs of incapacity to work.

Verbal decision analysis applied on the optimization of Alzheimer's disease diagnosis: a case study based on neuroimaging.

There is a great challenge in identifying the early diagnosis of the Alzheimer's disease, which has become the most frequent cause of dementia in the last few years, being responsible for 50% of the cases in western countries. The main focus of the work is the development of a multicriteria model for aiding in the decision making on the diagnosis of the Alzheimer's disease. It will be made by means of the Aranaú Tool, a decision support system mainly based on the ZAPROS method.