Machine learning and deep learning methods for skin lesion classification and diagnosis: a systematic review

MA Kassem, KM Hosny, R Damaševičius, MM Eltoukhy - Diagnostics, 2021 - mdpi.com
Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in develo** computer-aided diagnosis …

Computer vision for microscopic skin cancer diagnosis using handcrafted and non‐handcrafted features

T Saba - Microscopy Research and Technique, 2021 - Wiley Online Library
Skin covers the entire body and is the largest organ. Skin cancer is one of the most dreadful
cancers that is primarily triggered by sensitivity to ultraviolet rays from the sun. However, the …

Machine learning and deep learning algorithms for skin cancer classification from dermoscopic images

S Bechelli, J Delhommelle - Bioengineering, 2022 - mdpi.com
We carry out a critical assessment of machine learning and deep learning models for the
classification of skin tumors. Machine learning (ML) algorithms tested in this work include …

Deep LSTM with reinforcement learning layer for financial trend prediction in FX high frequency trading systems

F Rundo - Applied Sciences, 2019 - mdpi.com
High-frequency trading is a method of intervention on the financial markets that uses
sophisticated software tools, and sometimes also hardware, with which to implement high …

An innovative deep learning algorithm for drowsiness detection from EEG signal

F Rundo, S Rinella, S Massimino, M Coco, G Fallica… - Computation, 2019 - mdpi.com
The development of detection methodologies for reliable drowsiness tracking is a
challenging task requiring both appropriate signal inputs and accurate and robust …

The promise of digital biopsy for the prediction of tumor molecular features and clinical outcomes associated with immunotherapy

GL Banna, T Olivier, F Rundo, U Malapelle… - Frontiers in …, 2019 - frontiersin.org
Immunotherapy by immune checkpoint inhibitors has emerged as an effective treatment for a
slight proportion of patients with aggressive tumors. Currently, some molecular …

Ad-hoc shallow neural network to learn hyper filtered photoplethysmographic (ppg) signal for efficient car-driver drowsiness monitoring

F Rundo, C Spampinato, S Conoci - Electronics, 2019 - mdpi.com
In next-generation cars, safety equipment related to assisted driving systems commonly
known as ADAS (advanced driver-assistance systems) are of particular interest for the major …

LightSit: An unobtrusive health-promoting system for relaxation and fitness microbreaks at work

X Ren, B Yu, Y Lu, B Zhang, J Hu, A Brombacher - Sensors, 2019 - mdpi.com
Physical inactivity and chronic stress at work increase the risks of develo** metabolic
disorders, mental illnesses, and musculoskeletal injuries, threatening office workers' …

Proposed neural SAE-based medical image cryptography framework using deep extracted features for smart IoT healthcare applications

W El-Shafai, F Khallaf, ESM El-Rabaie… - Neural Computing and …, 2022 - Springer
Image cryptography based on chaos algorithms is widely employed in modern security
systems in telemedicine Internet of Things (IoT) applications. One of the main drawbacks of …

Advanced deep learning embedded motion radiomics pipeline for predicting anti-PD-1/PD-L1 immunotherapy response in the treatment of bladder cancer: preliminary …

F Rundo, C Spampinato, GL Banna, S Conoci - Electronics, 2019 - mdpi.com
A key objective of modern medicine is precision medicine, whose purpose is to personalize
the treatment based on the specific characteristics of the patients and their illness. To guide …