Features selected by optimization algorithms. حسب Afnan M. Alhassan (18349378)

Illustration of the transformed binary images of normal, benign, and malignant samples into grayscale. حسب Tehnan I. A. Mohamed (16846175)

Hybrid feature selection algorithm of CSCO-ROA. حسب Afnan M. Alhassan (18349378)

MLP vs classification algorithms. حسب Mohd Mustaqeem (19106494)

Algorithms and evaluation metrics integrated in the COPS framework. حسب Teemu J. Rintala (19333003)

Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning حسب Lu Xin (728966)

"…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. …"

Label-Free Assessment of the Drug Resistance of Epithelial Ovarian Cancer Cells in a Microfluidic Holographic Flow Cytometer Boosted through Machine Learning حسب Lu Xin (728966)

"…Several morphologic and texture features at a single-cell level have been extracted from the quantitative phase images. …"

Sample image for illustration. حسب Indhumathi S. (19173013)

"…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"

Table1_Identification of biomarkers for hepatocellular carcinoma based on single cell sequencing and machine learning algorithms.DOCX حسب Weimin Li (131040)

"…In this study, based on the scRNA-seq results of primary neoplastic cells and paired normal liver cells from eight HCC patients, a new strategy of machine learning algorithms was applied to screen core biomarkers that distinguished HCC tumor tissues from the adjacent normal liver. …"

Quadratic polynomial in 2D image plane. حسب Indhumathi S. (19173013)

"…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics حسب Zhichao Liu (191718)

"…Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …"

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics حسب Zhichao Liu (191718)

"…Recent developments in high-resolution mass spectrometry (HRMS) technology enabled ultrasensitive detection of proteins, peptides, and metabolites in limited amounts of samples, even single cells. However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …"

Proposed model tuned hyperparameters. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

The workflow of the proposed model. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

ResNeXt101 training and results. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Proposed model specificity and DSC outcomes. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Accuracy comparison of proposed and other models. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Architecture of ConvNet. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Comparison of state-of-the-art method. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"

Proposed model sensitivity outcome. حسب Subathra Gunasekaran (19492680)

"…To select the most informative features for effective segmentation, we utilize an advanced meta-heuristics algorithm called Advanced Whale Optimization (AWO). …"