Total mean square error (MSE) of training and experimental data in the best implementation of ANN-BTA network for estimating basic reproduction number related to COVID-19 patients... by Mouhamad Bodaghie (14838511)

Subjects:

The MSE value of ANN-BTA network after interval limiting [1,1.2] and obtaining the lowest error rate in estimating basic reproduction numberand. by Mouhamad Bodaghie (14838511)

Subjects:

Fig 8 - by Mouhamad Bodaghie (14838511)

Subjects:

Parameter space exploration in comparison to exploitation for the selection of samples during Bayesian Optimization. by John E. Fleming (8533956)

Distributions of model parameters mirror differentially expressed ion channel genes. by Daniele Linaro (227790)

Calibration plots for all models on the Derivation cohort. by Agni Orfanoudaki (8878097)

Graphical illustration of sample size estimation for the study protocol. by Müge Yalçin (16486563)

Most cost-effective option* when TCZ is available. by Gabrielle Bonnet (11614471)

Network propagation identifies ageing-associated genes as well as genes distinguishing prostate tumors of different grades. by Konstantina Charmpi (9901053)

Cluster survival results. by Teemu J. Rintala (19333003)

Cluster survival results with different pathway sets. by Teemu J. Rintala (19333003)

Overview of study assessments of the trial. by Tan Boon Toh (1348143)

“…A QPOP-guided treatment selection algorithm will then be used to select the most appropriate drug combination. …”

Performance of pairing prediction versus training set size and number of pairs per species. by Guillaume Marmier (7495823)

“…<p><b>A</b>: Fraction of pairs correctly identified (TP fraction) versus training set size, for DCA-, MI-, and Mirrortree-based methods. The three pairing scores corresponding to each of these three methods are employed in two ways: either within each species we find the chain B with optimal pairing score with each chain A (dashed lines), or within each species we employ the Hungarian matching algorithm to find the one-to-one pairing of chains A and B that optimizes the sum of the pairing scores (solid lines). …”

Human expert versus automated processing: Running dataset. by Keenon Werling (17512156)

Table 1_Developing and validating a drug recommendation system based on tumor microenvironment and drug fingerprint.xlsx by Yan Wang (15435)

“…This study aimed to develop a personalized drug recommendation model leveraging genomic profiles to optimize therapeutic outcomes.</p>Methods<p>A content-based filtering algorithm was implemented to predict drug sensitivity. …”

Table 2_Developing and validating a drug recommendation system based on tumor microenvironment and drug fingerprint.xlsx by Yan Wang (15435)

“…This study aimed to develop a personalized drug recommendation model leveraging genomic profiles to optimize therapeutic outcomes.</p>Methods<p>A content-based filtering algorithm was implemented to predict drug sensitivity. …”

Table 3_Developing and validating a drug recommendation system based on tumor microenvironment and drug fingerprint.xlsx by Yan Wang (15435)

“…This study aimed to develop a personalized drug recommendation model leveraging genomic profiles to optimize therapeutic outcomes.</p>Methods<p>A content-based filtering algorithm was implemented to predict drug sensitivity. …”

Video_1_Cabbage and Weed Identification Based on Machine Learning and Target Spraying System Design.MP4 by Xueguan Zhao (13197201)

“…With the image skeleton point-to-line ratio and ring structure features of support vector machine classification and identification, a contrast test of different feature combinations of a support vector machine was carried out, and the optimal feature combination of the support vector machine and its parameters were determined. …”

Additional file 2 of Machine learning-based prediction of antimicrobial resistance and identification of AMR-related SNPs in Mycobacterium tuberculosis by Yi Xu (131145)

“…Assessment of the performance of the optimal machine learning algorithms in predicting resistance to four first-line drugs in the external independent MTB isolates. …”

Table_4_Computed Tomography Imaging-Based Radiogenomics Analysis Reveals Hypoxia Patterns and Immunological Characteristics in Ovarian Cancer.xlsx by Songwei Feng (11200268)

“…Finally, optimal radiogenomics biomarkers for predicting the risk status of patients were developed by machine learning algorithms.…”