Alex Gaudio
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Performance of an artificial intelligence algorithm for interpreting lung sounds from children hospitalised with pneumonia in Malawi Open
This AI lung sound classification algorithm accurately identified abnormal lung sounds in children with severe pneumonia. Next steps include training the algorithm to identify uninterpretable recordings and different abnormal sounds.
Diaphragm Design for an Electret Microphone Stethoscope Open
This article investigates the design elements of a digital stethoscope and its signal fidelity in the presence of ambient noise. While the acoustic impedance matching literature demonstrates that signal pickup can improve when the diaphrag…
Separation of the Aortic and Pulmonary Components of the Second Heart Sound via Alternating Optimization Open
An algorithm for blind source separation (BSS) of the second heart sound (S2) into aortic and pulmonary components is proposed. It recovers aortic (A2) and pulmonary (P2) waveforms, as well as their relative delays, by solving an alternati…
<span><i>DeepFixCX</i></span>: Explainable privacy‐preserving image compression for medical image analysis Open
Explanations of a model's biases or predictions are essential to medical image analysis. Yet, explainable machine learning approaches for medical image analysis are challenged by needs to preserve privacy of patient data, and by current tr…
<span>ExplainFix</span>: Explainable spatially fixed deep networks Open
Is there an initialization for deep networks that requires no learning? ExplainFix adopts two design principles: the “fixed filters” principle that all spatial filter weights of convolutional neural networks can be fixed at initialization …
HeartSpot: Privatized and Explainable Data Compression for Cardiomegaly Detection Open
Advances in data-driven deep learning for chest X-ray image analysis underscore the need for explainability, privacy, large datasets and significant computational resources. We frame privacy and explainability as a lossy single-image compr…
A Massively-Parallel 3D Simulator for Soft and Hybrid Robots Open
Simulation is an important step in robotics for creating control policies and testing various physical parameters. Soft robotics is a field that presents unique physical challenges for simulating its subjects due to the nonlinearity of def…
View article: Privacy-Preserving Case-Based Explanations: Enabling Visual Interpretability by Protecting Privacy
Privacy-Preserving Case-Based Explanations: Enabling Visual Interpretability by Protecting Privacy Open
Deep Learning achieves state-of-the-art results in many domains, yet its black-box nature limits its application to real-world contexts. An intuitive way to improve the interpretability of Deep Learning models is by explaining their decisi…
O‐MedAL: Online active deep learning for medical image analysis Open
Active learning (AL) methods create an optimized labeled training set from unlabeled data. We introduce a novel online active deep learning method for medical image analysis. We extend our MedAL AL framework to present new results in this …