Search

Your search keyword '"Ali Hafiz"' showing total 1,019 results
Start Over Author "Ali Hafiz" Publication Year Range Last 3 years
1,019 results on '"Ali Hafiz"'

1. A novel extracellular vesicle paradigm for the treatment of COVID-19 induced acute respiratory distress syndrome (ARDS)

Author

Erik Osborn, John T. Ransom, Anastasiya Shulman, Vikram Sengupta, Mohammed Choudhry, Ali Hafiz, Jacob Gooden, and Amy L. Lightner

Subjects
Mesenchymal stem cell, MSC, Extracellular vesicle, EV, ARDS, Diseases of the respiratory system, RC705-779
Abstract

Efficacy of mesenchymal stem cells (MSCs) for treatment of acute respiratory distress syndrome (ARDS) suggests bioactive bone marrow MSC extracellular vesicles (BM-MSC EVs) may be effective. A patient with severe COVID-19 associated ARDS who was presumed to expire was treated with a BM-MSC EV preparation (14 doses over two months) as a rescue treatment for refractory COVID ARDS. Near complete reversal of lung inflammation and fibrosis (per computed tomography), near complete restoration of mobility, hospital discharge (3 months) with resumption of normal activities of daily living (one year) and return to work occurred. No adverse events occurred despite repeated dosing of investigational product, highlighting safety of this potential therapy for ARDS.

Published
2024
Full Text
View/download PDF

2. Feasibility of tele-guided patient-administered lung ultrasound in heart failure

Author

Ariella Pratzer, Eugene Yuriditsky, Tajinderpal Saraon, Michael Janjigian, Ali Hafiz, Jun-Chieh J. Tsay, Pamela Boodram, Nikita Jejurikar, and Harald Sauthoff

Subjects
Lung ultrasound, Tele-guidance, Patient-performed, Heart failure, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background Readmission rates for heart failure remain high, and affordable technology for early detection of heart failure decompensation in the home environment is needed. Lung ultrasound has been shown to be a sensitive tool to detect pulmonary congestion due to heart failure, and monitoring patients in their home environment with lung ultrasound could help to prevent hospital admissions. The aim of this project was to investigate whether patient-performed tele-guided ultrasound in the home environment using an ultraportable device is feasible.Affiliations: Journal instruction requires a country for affiliations; however, these are missing in affiliations [1, 2]. Please verify if the provided country are correct and amend if necessary.Correct Methods Stable ambulatory patients with heart failure received a handheld ultrasound probe connected to a smart phone or tablet. Instructions for setup were given in person during a clinic visit or over the phone. During each ultrasound session, patients obtained six ultrasound clips from the anterior and lateral chest with verbal and visual tele-guidance from an ultrasound trained clinician. Patients also reported their weight and degree of dyspnea, graded on a 5-point scale. Two independent reviewers graded the ultrasound clips based on the visibility of the pleural line and A or B lines. Results Eight stable heart failure patients each performed 10–12 lung ultrasound examinations at home under remote guidance within a 1-month period. There were no major technical difficulties. A total of 89 ultrasound sessions resulted in 534 clips of which 88% (reviewer 1) and 84% (reviewer 2) were interpretable. 91% of ultrasound sessions produced interpretable clips bilaterally from the lateral chest area, which is most sensitive for the detection of pulmonary congestion. The average time to complete an ultrasound session was 5 min with even shorter recording times for the last session. All patients were clinically stable during the study period and no false positive B-lines were observed. Conclusions In this feasibility study, patients were able to produce interpretable lung ultrasound exams in more than 90% of remotely supervised sessions in their home environment. Larger studies are needed to determine whether remotely guided lung ultrasound could be useful to detect heart failure decompensation early in the home environment.

Published
2023
Full Text
View/download PDF

15. Deep Neural Network Models Trained With A Fixed Random Classifier Transfer Better Across Domains

Author

Ali, Hafiz Tiomoko, Michieli, Umberto, Moon, Ji Joong, Kim, Daehyun, and Ozay, Mete

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing
Abstract

The recently discovered Neural collapse (NC) phenomenon states that the last-layer weights of Deep Neural Networks (DNN), converge to the so-called Equiangular Tight Frame (ETF) simplex, at the terminal phase of their training. This ETF geometry is equivalent to vanishing within-class variability of the last layer activations. Inspired by NC properties, we explore in this paper the transferability of DNN models trained with their last layer weight fixed according to ETF. This enforces class separation by eliminating class covariance information, effectively providing implicit regularization. We show that DNN models trained with such a fixed classifier significantly improve transfer performance, particularly on out-of-domain datasets. On a broad range of fine-grained image classification datasets, our approach outperforms i) baseline methods that do not perform any covariance regularization (up to 22%), as well as ii) methods that explicitly whiten covariance of activations throughout training (up to 19%). Our findings suggest that DNNs trained with fixed ETF classifiers offer a powerful mechanism for improving transfer learning across domains., Comment: ICASSP 2024. Copyright 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other

Published
2024

28. Introduction

Author

Ejaz, Faheem, Pao, William, Ali, Hafiz Muhammad, Ejaz, Faheem, Pao, William, and Ali, Hafiz Muhammad

Published
2024
Full Text
View/download PDF

34. AI-Based Emotion Recognition: Promise, Peril, and Prescriptions for Prosocial Path

Author

Latif, Siddique, Ali, Hafiz Shehbaz, Usama, Muhammad, Rana, Rajib, Schuller, Björn, and Qadir, Junaid

Subjects
Computer Science - Human-Computer Interaction
Abstract

Automated emotion recognition (AER) technology can detect humans' emotional states in real-time using facial expressions, voice attributes, text, body movements, and neurological signals and has a broad range of applications across many sectors. It helps businesses get a much deeper understanding of their customers, enables monitoring of individuals' moods in healthcare, education, or the automotive industry, and enables identification of violence and threat in forensics, to name a few. However, AER technology also risks using artificial intelligence (AI) to interpret sensitive human emotions. It can be used for economic and political power and against individual rights. Human emotions are highly personal, and users have justifiable concerns about privacy invasion, emotional manipulation, and bias. In this paper, we present the promises and perils of AER applications. We discuss the ethical challenges related to the data and AER systems and highlight the prescriptions for prosocial perspectives for future AER applications. We hope this work will help AI researchers and developers design prosocial AER applications., Comment: Under review in IEEE TAC

Published
2022

36. Numerical Evaluation of Crack in the Nuclear Reactor Pressure Vessel Using Extended Finite Element Method Technique

Author

Aslam, Muhammad Moazam, Ahmad, Atique, Yaqoob, Haseeb, Muhammad Ali, Hafiz, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Tolio, Tullio A. M., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Schmitt, Robert, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Shams, Afaque, editor, Al-Athel, Khaled, editor, Tiselj, Iztok, editor, Pautz, Andreas, editor, and Kwiatkowski, Tomasz, editor

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results