Data-centric artificial intelligence: A survey
Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …
of its great success is the availability of abundant and high-quality data for building machine …
Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
A hybrid dipper throated optimization algorithm and particle swarm optimization (DTPSO) model for hepatocellular carcinoma (HCC) prediction
Hepatocellular carcinoma (HCC) is a form of liver cancer that is widespread in Europe,
Africa, and Asia. The early identification of HCC is critical in improving the likelihood of …
Africa, and Asia. The early identification of HCC is critical in improving the likelihood of …
Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping
In this research, eight individual machine learning and statistical models are implemented
and compared, and based on their results, seven ensemble models for flood susceptibility …
and compared, and based on their results, seven ensemble models for flood susceptibility …
A novel chaos-based privacy-preserving deep learning model for cancer diagnosis
Early cancer identification is regarded as a challenging problem in cancer prevention for the
healthcare community. In addition, ensuring privacy-preserving healthcare data becomes …
healthcare community. In addition, ensuring privacy-preserving healthcare data becomes …
Machine learning models for the identification of prognostic and predictive cancer biomarkers: a systematic review
The identification of biomarkers plays a crucial role in personalized medicine, both in the
clinical and research settings. However, the contrast between predictive and prognostic …
clinical and research settings. However, the contrast between predictive and prognostic …
A review on face recognition systems: recent approaches and challenges
Face recognition is an efficient technique and one of the most preferred biometric modalities
for the identification and verification of individuals as compared to voice, fingerprint, iris …
for the identification and verification of individuals as compared to voice, fingerprint, iris …
[HTML][HTML] Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)
Recently, numerous studies have been conducted on Missing Value Imputation (MVI),
intending the primary solution scheme for the datasets containing one or more missing …
intending the primary solution scheme for the datasets containing one or more missing …
Accurate and Convenient Lung Cancer Diagnosis through Detection of Extracellular Vesicle Membrane Proteins via Förster Resonance Energy Transfer
S Xiao, Y Yao, S Liao, B Xu, X Li, Y Zhang, L Zhang… - Nano …, 2023 - ACS Publications
Tumor-derived extracellular vesicles (EVs) are promising to monitor early stage cancer.
Unfortunately, isolating and analyzing EVs from a patient's liquid biopsy are challenging. For …
Unfortunately, isolating and analyzing EVs from a patient's liquid biopsy are challenging. For …
Machine-learning-based similarity meets traditional QSAR:“q-RASAR” for the enhancement of the external predictivity and detection of prediction confidence outliers …
A Banerjee, K Roy - Chemometrics and Intelligent Laboratory Systems, 2023 - Elsevier
Recently, the concept of quantitative Read-Across Structure-Activity Relationship (q-RASAR)
has been introduced by using various Machine Learning (ML)-derived similarity functions in …
has been introduced by using various Machine Learning (ML)-derived similarity functions in …