Artificial intelligence for breast cancer analysis: Trends & directions

SM Shah, RA Khan, S Arif, U Sajid - Computers in Biology and Medicine, 2022 - Elsevier
Breast cancer is one of the leading causes of death among women. Early detection of breast
cancer can significantly improve the lives of millions of women across the globe. Given …

The systematic review of artificial intelligence applications in breast cancer diagnosis

D Uzun Ozsahin, D Ikechukwu Emegano, B Uzun… - Diagnostics, 2022 - mdpi.com
Several studies have demonstrated the value of artificial intelligence (AI) applications in
breast cancer diagnosis. The systematic review of AI applications in breast cancer diagnosis …

Learning facial expression and body gesture visual information for video emotion recognition

J Wei, G Hu, X Yang, AT Luu, Y Dong - Expert Systems with Applications, 2024 - Elsevier
Recent research has shown that facial expressions and body gestures are two significant
implications in identifying human emotions. However, these studies mainly focus on …

A novel machine learning based framework for detection of autism spectrum disorder (ASD)

H Sharif, RA Khan - Applied Artificial Intelligence, 2022 - Taylor & Francis
ABSTRACT Autism Spectrum Disorder (ASD) is linked with abridged ability in social
behavior. Scientists working in the broader domain of cognitive sciences have done a lot of …

Breast cancer classification using deep learned features boosted with handcrafted features

U Sajid, RA Khan, SM Shah, S Arif - Biomedical Signal Processing and …, 2023 - Elsevier
Breast cancer is one of the leading causes of death among women across the globe. It is
difficult to treat if detected at advanced stages. However, early detection can significantly …

Modeling multiple temporal scales of full-body movements for emotion classification

C Beyan, S Karumuri, G Volpe… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
This article investigates classification of emotions from full-body movements by using a
novel Convolutional Neural Network-based architecture. The model is composed of two …

Graph laplacian-improved convolutional residual autoencoder for unsupervised human action and emotion recognition

G Paoletti, C Beyan, A Del Bue - IEEE Access, 2022 - ieeexplore.ieee.org
This paper presents an unsupervised feature learning approach based on 3D-skeleton data
for human action and human discrete emotion recognition. Relying on the time series of …

Emotion Recognition From Full-Body Motion Using Multiscale Spatio-Temporal Network

T Wang, S Liu, F He, W Dai, M Du… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Body motion is an important channel for human communication and plays a crucial role in
automatic emotion recognition. This work proposes a multiscale spatio-temporal network …

Emotion expression in human body posture and movement: A survey on intelligible motion factors, quantification and validation

MA Mahfoudi, A Meyer, T Gaudin… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Many areas in computer science are facing the need to analyze, quantify and reproduce
movements expressing emotions. This paper presents a systematic review of the intelligible …

Affective body expression recognition framework based on temporal and spatial fusion features

T Wang, S Liu, F He, M Du, W Dai, Y Ke… - Knowledge-Based Systems, 2025 - Elsevier
Affective body expression recognition technology enables machines to interpret non-verbal
emotional signals from human movements, which is crucial for facilitating natural and …