Sentence examples for features to predict a from inspiring English sources
We examined the ability of lake and landscape features to predict a variety of macrophyte cover metrics using 54 north temperate lakes.
5 Briefly, we used five ultrasonic features to predict a malignant tumour (M features): irregular solid tumour (M1), ascites (M2), at least four papillary structures (M3), irregular multilocular solid tumour with a largest diameter of at least 100 mm (M4), and very high colour content on colour Doppler examination (M5).
We used five ultrasonic features to predict a benign tumour (B features): unilocular cyst (B1), presence of solid components for which the largest solid component is <7 mm in largest diameter (B2), acoustic shadows (B3), smooth multilocular tumour (B4), and no detectable blood flow on Doppler examination (B5).
Here, we define a molecular signature as a set of biomolecular features (e.g. DNA sequence, DNA copy number, RNA, protein, and metabolite expression) together with a predefined computational procedure that applies those features to predict a phenotype of clinical interest on a previously unseen patient sample.
Infants bias intrinsic features to predict an object's future behavior.
A Tesla car appears to have successfully used its Autopilot feature to predict a car crash moments before it happened, according to dashcam footage released this week.
We developed a computer-vision algorithm capable of extracting 113 features from magnification views in mammograms and combining these features to predict whether a DCIS case will be upstaged to invasive cancer at the time of definitive surgery.
In other words, we theorized prebaseline built-environment features to predict both a) physical functioning at 24 months and b) social support at baseline.
PolyPhen-2 [ 9] used eight sequence-based and three structure-based features to predict the impact of a mutation/polymorphism and used naive Bayes as a statistical classifier.
Naveed [7] used a learning approach based on pure content features to predict the probability of a message being retweeted.
However, authors used the properties of a voter's social network as input features to predict the sign of a vote given by participants of the election.
