Miguel Nobre Menezes

Lecturer; Clinical Research Investigator

Universidade do Porto Faculdade de Medicina

Portugal

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Miguel Nobre Menezes is a Lecturer and Clinical Research Investigator at Universidade de Lisboa Faculdade de Medicina in Portugal. His research areas include systemic amyloidosis diagnosis, coronary microvascular disease, and the application of artificial intelligence in cardiovascular medicine. Recent publications highlight his focus on advanced imaging techniques and the efficacy of innovative diagnostic methods in cardiology.

Miguel Nobre Menezes

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Articles (25)

Non-invasive derivation of instantaneous free-wave ratio from invasive coronary angiography using a new deep learning artificial intelligence model and comparison with human operators’ performance

Challenges in Diagnosing Systemic Amyloidosis.

Multimodality Imaging in the Diagnosis of Coronary Microvascular Disease: An Update.

Old Habits Die Hard: Can AI Help Bring Coronary Angiography Into the 21st Century?

A Narrative Review of Revascularization in Chronic Coronary Syndrome/Disease: Concepts and Misconceptions.

Comparison of the accuracy of four diagnostic prediction rules for pulmonary embolism in patients admitted to the emergency department.

Coronary Intravascular Lithotripsy Effectiveness and Safety in a Real-World Cohort

PCI in Cancer Patients: Adding Another Piece to a Complex and Still Very Incomplete Puzzle.

Coronary physiology instantaneous wave-free ratio (iFR) derived from x-ray angiography using artificial intelligence deep learning models: a pilot study.

Enhancing Diagnostic Precision: Intracardiac Echocardiography-Guided Endomyocardial Biopsy for Complex Right Atrial Mass.

Effects of radial artery spasm prophylaxis on intracoronary vasomotor responses during acetylcholine spasm provocation testing.

Digital health in cardiovascular medicine: An overview of key applications and clinical impact by the Portuguese Society of Cardiology Study Group on Digital Health.

Segmentation of X‐ray coronary angiography with an artificial intelligence deep learning model: Impact in operator visual assessment of coronary stenosis severity

Coronary X-ray angiography segmentation using Artificial Intelligence: a multicentric validation study of a deep learning model.

Artificial intelligence-based diagnosis of acute pulmonary embolism: Development of a machine learning model using 12-lead electrocardiogram.

The cusp-overlap technique for reducing pacemaker implantation after transcatheter aortic valve implantation: Game-changer or gimmick?

Cardiovascular Health Metrics Differ Between Individuals With and Without Cancer

Coronary Artery Calcium Identified on Non-Gated Chest CT Scans: A Wasted Opportunity for Preventive Cardiological Care.

Interventional cardiology in cancer patients: A position paper from the Portuguese Cardiovascular Intervention Association and the Portuguese Cardio-Oncology Study Group of the Portuguese Society of Cardiology.

Stenosis Detection in X-ray Coronary Angiography with Deep Neural Networks Leveraged by Attention Mechanisms

Clinical experience of a cardio-oncology consultation at a tertiary university hospital in Portugal: An observational study.

Development of deep learning segmentation models for coronary X-ray angiography: Quality assessment by a new global segmentation score and comparison with human performance.

Rapidly Progressive Coronary Aneurysm: A Rare Case of Isolated Coronary Vasculitis With Recurrent Myocardial Infarction.

There's more to a coronary thrombus than just platelets and fibrin - a new potential therapeutic target in the form of SGK-1 modulation?

Collaborators (4)

Ana Gomes de Almeida

Mamas A. Mamas

Fausto J. Pinto

Arlindo Oliveira

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