One advantage of our algorithm is that it is not binary in nature. by Yong Kuk Kim (13955214)

Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

“…In general, BRBPNN does not show any optimization adaption methods to determine the optimal parameter for appropriate detection. Hence, Binary Black Widow Optimization Algorithm (BBWOA) is proposed in this manuscript to improve the BRBPNN classifier that detects intrusion precisely. …”

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

Data set constituents. by Rémy Peyret (14691736)

“…We then performed a calibration step based on transfer learning to maintain the performance when translating on a new target acquisition center by using a limited amount of additional training data. Performance was evaluated using classical binary measures (accuracy, recall, precision) for both centers (referred to as “test reference dataset” and “test target dataset”) and at two levels: patch and slide level. …”

Results of the model on test sets 1 and 2. by Rémy Peyret (14691736)

“…We then performed a calibration step based on transfer learning to maintain the performance when translating on a new target acquisition center by using a limited amount of additional training data. Performance was evaluated using classical binary measures (accuracy, recall, precision) for both centers (referred to as “test reference dataset” and “test target dataset”) and at two levels: patch and slide level. …”

Scanners and staining methods. by Rémy Peyret (14691736)

“…We then performed a calibration step based on transfer learning to maintain the performance when translating on a new target acquisition center by using a limited amount of additional training data. Performance was evaluated using classical binary measures (accuracy, recall, precision) for both centers (referred to as “test reference dataset” and “test target dataset”) and at two levels: patch and slide level. …”

Data_Sheet_1_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.DOCX by Changho Han (1309563)

Data Sheet 1_Development of a two-stage depression symptom detection model: application of neural networks to twitter data.docx by Faye Beatriz Tumaliuan (20394737)

“…Limitations on misclassifications, negation, and data imbalance and biases can be addressed in future studies.…”

Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx by Changjiang Liang (21099887)

Supplementary Material for: Detecting atrial fibrillation by artificial intelligence enabled neuroimaging examination. by figshare admin karger (2628495)

“…Background Diagnosis of occult atrial fibrillation (AF) is difficult as it is often asymptomatic, leading to under detection. Current diagnostic tests have variable limitations in feasibility and accuracy. …”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”

Raw LC-MS/MS and RNA-Seq Mitochondria data by Stefano Martellucci (16284377)

“…The missing values were imputed with the minimum intensity value for each specific data set; (b) for samples expressed in both scLRP1+/+ and scLRP1-/- tissue, the filtering process required 2 or more proteins to be detected in both scLRP1+/+ and scLRP1-/- samples. …”

Table 1_Non-obtrusive monitoring of obstructive sleep apnea syndrome based on ballistocardiography: a preliminary study.docx by Biyong Zhang (20906192)

“…This can reduce both the data to be stored or transmitted and the computational load. …”