Inferring ECG Waveforms from PPG Signals with a Modified U-Net Neural Network.

There are two widely used methods to measure the cardiac cycle and obtain heart rate measurements: the electrocardiogram (ECG) and the photoplethysmogram (PPG). The sensors used in these methods have gained great popularity in wearable devices, which have extended cardiac monitoring beyond the hospital environment. However, the continuous monitoring of ECG signals via mobile devices is challenging, as it requires users to keep their fingers pressed on the device during data collection, making it unfeasible in the long term.

Automatic classification of pulmonary nodules in computed tomography images using pre-trained networks and bag of features.

Lung cancer has the highest incidence in the world. The standard tests for its diagnostics are medical imaging exams, sputum cytology, and lung biopsy. Computed Tomography (CT) of the chest plays an essential role in the early detection of nodules since it can allow for more treatment options and increases patient survival.

A ensemble methodology for automatic classification of chest X-rays using deep learning.

Chest radiographies, or chest X-rays, are the most standard imaging exams used in daily hospitals. Responsible for assisting in detecting numerous pathologies and findings that directly interfere in the patient's life, this exam is therefore crucial in screening patients. This work proposes a methodology based on a Convolutional Neural Networks (CNNs) ensemble to aid the diagnosis of chest X-ray exams by screening them with a high probability of being normal or abnormal.

Classification of COVID-19 in X-ray images with Genetic Fine-tuning.

New and more transmissible SARS-COV-2 variants aggravated the SARS-COV-2 emergence. Lung X-ray images stand out as an alternative to support case screening. The latest computer-aided diagnosis systems have been using Deep Learning (DL) to detect pulmonary diseases.

Diagnosis of Leukaemia in Blood Slides Based on a Fine-Tuned and Highly Generalisable Deep Learning Model.

Leukaemia is a dysfunction that affects the production of white blood cells in the bone marrow. Young cells are abnormally produced, replacing normal blood cells. Consequently, the person suffers problems in transporting oxygen and in fighting infections.

Recent computational methods for white blood cell nuclei segmentation: A comparative study.

Background And Objective: Leukaemia is a disease found worldwide; it is a type of cancer that originates in the bone marrow and is characterised by an abnormal proliferation of white blood cells (leukocytes). In order to correctly identify this abnormality, haematologists examine blood smears from patients. A diagnosis obtained by this method may be influenced by factors such as the experience and level of fatigue of the haematologist, resulting in non-standard reports and even errors.

Lemierre syndrome: case report.

Lemierre syndrome is characterized by septic thrombophlebitis of the internal jugular vein, after an oropharyngeal infection, with septic embolization to the lungs or other organs. This case report describes a 37-year-old female patient who presented with edema and pain in the right hemiface with onset 3 days previously and progressive fatigue and dyspnea since the previous day. She had had tooth 48 extracted 3 days previously.

RELATIONSHIP BETWEEN THE PRESENCE OF HELICOBACTER PYLORI WITH INFLAMMATORY ENDOSCOPIC CHANGES IN GASTRODUODENAL MUCOSA.

Background: The influence of Helicobacter pylori (HP) in inflammatory disorders of the digestive mucosa has been the subject of several studies since socioeconomic, personal and environmental factors were implicated in the bacteria transmission.

Aim: To correlate the inflammatory endoscopic findings with HP infection and the onset of mucosal diseases mucous of the upper digestive tract.

Method: Comparative observational study, in which were collected data from 2247 patients who underwent upper endoscopy and biopsies for HP with urease test.