Weakly Semi-supervised Detector-based Video Classification with Temporal Context for Lung Ultrasound

GY Li, L Chen, M Zahiri, N Balaraju… - Proceedings of the …, 2023 - openaccess.thecvf.com
For many challenging medical imaging tasks involving sequences, video-level labels alone
are insufficient to train accurate disease classification models and do not carry information …

XCovNet: An optimized xception convolutional neural network for classification of COVID-19 from point-of-care lung ultrasound images

G Madhu, S Kautish, Y Gupta, G Nagachandrika… - Multimedia Tools and …, 2024 - Springer
Global livelihoods are impacted by the novel coronavirus (COVID-19) disease, which mostly
affects the respiratory system and spreads via airborne transmission. The disease has …

Breathe out the secret of the lung: video classification of exhaled flows from normal and asthmatic lung models using CNN-Long Short-Term Memory networks

M Talaat, X Si, J Xi - Journal of Respiration, 2023 - mdpi.com
In this study, we present a novel approach to differentiate normal and diseased lungs based
on exhaled flows from 3D-printed lung models simulating normal and asthmatic conditions …

How good are synthetic medical images? an empirical study with lung ultrasound

M Yu, S Kulhare, C Mehanian, CB Delahunt… - … Workshop on Simulation …, 2023 - Springer
Acquiring large quantities of data and annotations is effective for developing high-
performing deep learning models, but is difficult and expensive to do in the healthcare …

Automated diagnosis of respiratory diseases from lung ultrasound videos ensuring XAI: an innovative hybrid model approach

AI Abian, MA Khan Raiaan, A Karim, S Azam… - Frontiers in Computer …, 2024 - frontiersin.org
Introduction An automated computerized approach can aid radiologists in the early
diagnosis of lung disease from video modalities. This study focuses on the difficulties …

Using Deep Learning and MobileNet50V2 CNN Model to Classify Chest X-Ray Images for Pneumonia Disease Detection

KS Gill, V Anand, R Chauhan… - 2023 2nd International …, 2023 - ieeexplore.ieee.org
Pneumonia is a pathological condition characterised by the inflammation of the alveoli in
either one or both lungs. Symptoms including productive cough, fever, chills, and dyspnea …

Concept Complement Bottleneck Model for Interpretable Medical Image Diagnosis

H Wang, J Hou, H Chen - arXiv preprint arXiv:2410.15446, 2024 - arxiv.org
Models based on human-understandable concepts have received extensive attention to
improve model interpretability for trustworthy artificial intelligence in the field of medical …

Can Crowdsourced Annotations Improve AI-Based Congestion Scoring for Bedside Lung Ultrasound?

A Asgari-Targhi, T Ungi, M Jin, N Harrison… - … Conference on Medical …, 2024 - Springer
Lung ultrasound (LUS) has become an indispensable tool at the bedside in emergency and
acute care settings, offering a fast and non-invasive way to assess pulmonary congestion. Its …

[PDF][PDF] Detection and classification of pneumonia using the Orange3 data mining tool.

M Altayeb, A Arabiat, A Al-Ghraibah - International Journal of …, 2024 - researchgate.net
A chest X-ray can convey a lot about a patient's condition. However, it requires a specialized
and skilled doctor to determine the type of lung disease with high accuracy. Here comes the …

Transfer Learning and Feature Extraction of Chest X-ray Images for Deep Convolutional Neural Network (CNN)-based Pneumonia Detection

KS Gill, V Anand, R Gupta - 2023 4th IEEE Global Conference …, 2023 - ieeexplore.ieee.org
Pneumonia is a lung inflammation that mostly affects the tiny air sacs known as alveoli. A
productive or dry cough, chest discomfort, a fever, and breathing difficulties are typical …