Deep learning and machine learning in psychiatry: a survey of current progress in depression detection, diagnosis and treatment

M Squires, X Tao, S Elangovan, R Gururajan, X Zhou… - Brain Informatics, 2023 - Springer
Informatics paradigms for brain and mental health research have seen significant advances
in recent years. These developments can largely be attributed to the emergence of new …

[HTML][HTML] A novel stacking ensemble for detecting three types of diabetes mellitus using a Saudi Arabian dataset: pre-diabetes, T1DM, and T2DM

M Gollapalli, A Alansari, H Alkhorasani… - Computers in Biology …, 2022 - Elsevier
Glucose is the primary source of energy for cells, which are the building blocks of life. It is
given to the body by insulin that carries out the metabolic tasks that keep people alive …

Compressive strength prediction of lightweight concrete: Machine learning models

A Kumar, HC Arora, NR Kapoor, MA Mohammed… - Sustainability, 2022 - mdpi.com
Concrete is the most commonly used construction material. The physical properties of
concrete vary with the type of concrete, such as high and ultra-high-strength concrete, fibre …

CAM-VT: A weakly supervised cervical cancer nest image identification approach using conjugated attention mechanism and visual transformer

Z Fan, X Wu, C Li, H Chen, W Liu, Y Zheng… - Computers in Biology …, 2023 - Elsevier
Cervical cancer is the fourth most common cancer among women, and cytopathological
images are often used to screen for this cancer. However, manual examination is very …

[HTML][HTML] A novel ensemble-based statistical approach to estimate daily wildfire-specific PM2. 5 in California (2006–2020)

R Aguilera, N Luo, R Basu, J Wu, R Clemesha… - Environment …, 2023 - Elsevier
Though fine particulate matter (PM 2.5) has decreased in the United States (US) in the past
two decades, the increasing frequency, duration, and severity of wildfires significantly …

Modeling climate change impact on inflow and hydropower generation of Nangbeto dam in West Africa using multi-model CORDEX ensemble and ensemble machine …

S Obahoundje, A Diedhiou, L Dubus, EA Alamou… - Applied Energy, 2022 - Elsevier
Climate change (CC) poses a threat to renewable hydropower, which continues to play a
significant role in energy generation in West Africa (WA). Thus, the assessment of the …

[PDF][PDF] Ensemble-based face expression recognition approach for image sentiment analysis

EG Moung, CC Wooi, MM Sufian, CK On… - International Journal of …, 2022 - academia.edu
Sentiment analysis based on images is an evolving area of study. Developing a reliable
facial expression recognition (FER) device remains a difficult challenge as recognizing …

An automated system for ECG arrhythmia detection using machine learning techniques

M Sraitih, Y Jabrane, A Hajjam El Hassani - Journal of Clinical Medicine, 2021 - mdpi.com
The new advances in multiple types of devices and machine learning models provide
opportunities for practical automatic computer-aided diagnosis (CAD) systems for ECG …

Predicting outcome of traumatic brain injury: is machine learning the best way?

R Bruschetta, G Tartarisco, LF Lucca, E Leto, M Ursino… - Biomedicines, 2022 - mdpi.com
One of the main challenges in traumatic brain injury (TBI) patients is to achieve an early and
definite prognosis. Despite the recent development of algorithms based on artificial …

Development of an efficient cement production monitoring system based on the improved random forest algorithm

H Zermane, A Drardja - The International Journal of Advanced …, 2022 - Springer
Strengthening production plants and process control functions contribute to a global
improvement of manufacturing systems because of their cross-functional characteristics in …