ライフサイエンスコーパス: automated detection

1 ally disposable and can carry out in situ or automated detection.

2 The automated detection agreed with expert interpretation of

3 sis or a back-propagation neural network, an automated detection algorithm can be developed with data

4 We applied an automated detection algorithm to assess hourly presence

5 d we compared their performance with that of automated detection algorithms in data from middle- to o

6 rary, we characterise the performance of two automated detection algorithms that have been commonly u

7 tegrates high-content live-cell imaging with automated detection and analysis of fluorescent reporter

8 ds for the observational study of behaviour, automated detection and analysis of social interaction n

9 ds for the observational study of behaviour, automated detection and analysis of social interaction n

10 al techniques are presently available for an automated detection and analysis of subsystem variants.

11 tate of molecular processes within the cell, automated detection and analysis of these processes, and

12 uorescent plate/slide imaging technology and automated detection and analysis software, we were able

13 erarchical machine learning approach for the automated detection and classification of DV lesions in

14 his work we develop deep learning method for automated detection and classification of early AMD OCT

15 (CNN) were explicitly trained for performing automated detection and classification of hyperreflectiv

16 Purpose To develop a DL model for automated detection and classification of lumbar central

17 The MCI algorithm may be valuable toward the automated detection and diagnosis of COPD on chest CT sc

18 s immense potential for early, accurate, and automated detection and discrimination of malaria and de

19 A fully automated detection and grading network based on deep le

20 that deep learning can be used for the fully automated detection and grading of urothelial cell carci

21 ent a novel "deploy-and-forget" approach for automated detection and localization of damage in struct

22 novel multitask deep learning framework for automated detection and localization of endoleaks at aor

23 ges of 12-lead electrocardiograms (ECGs) for automated detection and prediction of multiple SHDs usin

24 ity slab to generate en face OCTA images for automated detection and quantification of RNV membrane a

25 able to semiautomated random acquisition and automated detection and quantification.

26 Real-time automated detection and quantitation of the bacteria are

27 computational expert teams to develop robust automated detection and segmentation methods in a crowd-

28 ist treating physicians in aSAH by providing automated detection and segmentations of aneurysms.

29 Objective automated detection and severity classification of dysar

30 igorous but flexible definition and accurate automated detection and tracking of geometric features o

31 dy illustrates how UAS, thermal imagery, and automated detection can be combined to efficiently colle

32 ctures analysis program) to enable rapid and automated detection, classification and quantification o

33 We demonstrate fully automated detection for both experimental and simulated

34 to accelerate the editing and annotating of automated detections from extensive acoustic datasets.

35 We found atrial fibrillation using automated detection (>/= 90 s in 30 min) and classed as

36 r systems, which enhances the scalability of automated detection in dynamic aquatic environments.

37 ed by meat cutters without special training, automated detection is needed.

38 l marker, there currently exists no standard automated detection method.

39 l research contributes to the refinement the automated detection methodologies of hepatic steatosis o

40 ulation, using both semi-automated and fully automated detection methods, and that this biomarker out

41 ase MR images can be obtained routinely with automated detection of a contrast material bolus.

42 This strategy enables the automated detection of a wide variety of nonphysical sig

43 e dynamics as an objective biomarker for the automated detection of ADHD.

44 e-scale typing schemes, and it enables rapid automated detection of antimicrobial resistance and viru

45 illaric circuit (CC) optimized for rapid and automated detection of bacteria in urine.

46 easibility of the approach for real-time and automated detection of bacterial contamination in food s

47 The application of WDM for rapid, automated detection of bacterial DNA from whole blood ma

48 sis of HSI data resulted in >90% accuracy of automated detection of BD.

49 Annotation System (BBAS), which enables the automated detection of bees' behaviours in small observa

50 s system open avenues for the development of automated detection of biomolecules at the nanoliter sca

51 successfully optimized reference regions for automated detection of brain imaging tracers.

52 Automated detection of calls is essential to bioacoustic

53 ansgenic H2B-mCherry system for unequivocal, automated detection of cardiomyocyte nuclei.

54 ate image information is a powerful tool for automated detection of cell morphology changes.

55 Automated detection of colonic polyps, especially clinic

56 This paper presents a method for automated detection of complex (non-self-avoiding) postu

57 Automated detection of complex animal behaviors remains

58 hanced MR angiographic studies obtained with automated detection of contrast agent arrival.

59 Automated detection of decreases in SDAAM was 70% sensit

60 nces with nanometer-scale resolution and the automated detection of defects and edges, as well as det

61 ply deep learning to create an algorithm for automated detection of diabetic retinopathy and diabetic

62 g computerized image analysis algorithms for automated detection of disease extent from digital patho

63 Here we describe software tools for the automated detection of DNA restriction fragments resolve

64 a obtained at rest was used as a control for automated detection of dobutamine-induced wall motion ab

65 ulted in computer algorithms that allow near automated detection of endocardial boundaries and measur

66 relation between counts by visual raters and automated detection of ePVSs in the same section (r = 0.

67 llation, intracranial volume estimation, and automated detection of faulty segmentations (mainly caus

68 rsus that of a retina specialist (RS) in the automated detection of fluid on optical coherence tomogr

69 interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving

70 Using this system, we demonstrate the automated detection of four classes of CBW agent simulan

71 ing model demonstrated high accuracy for the automated detection of GA.

72 roduce a new deep learning framework for the automated detection of GFAP-immunolabeled astrocytes in

73 er can augment these efforts by enabling the automated detection of gonotrophic stages of mosquitoes

74 arning-based annotation tools and enable the automated detection of hairpin loops and structural anom

75 Following the previous report of a semi-automated detection of HTR based on the dynamics of mous

76 Outcomes after an automated detection of impending clinical deterioration

77 e structure, make them appealing targets for automated detection of individual cells.

78 s, providing a potential route for real-time automated detection of irregular environmental behavior

79 a control dataset, we developed a method for automated detection of key nodes in the motor network, i

80 g applications for imaging of AIS, including automated detection of large vessel occlusion and measur

81 tive digital immune landscape while enabling automated detection of major inflammatory clusters and c

82 three-dimensional resolution, which enabled automated detection of multicellular tissue architecture

83 This framework enables the automated detection of multiple factors and understandin

84 sequences and respiratory motion, fast near-automated detection of myocardial segments and accurate

85 orithm analytic platform (ventMAP) to enable automated detection of off-target ventilation (OTV) deli

86 nvolutional neural network (CNN) cascade for automated detection of particles in cryo-electron microg

87 Automated detection of patients with such risks via a re

88 In fully automated detection of PCa patients, deep learning had a

89 r analysis of retinal photographs for DR and automated detection of RDR can be implemented safely int

90 ibility of the current method for completely automated detection of reactive metabolites via computer

91 rate 2 clinically relevant applications: the automated detection of recurrent bleeding and appropriat

92 In protocol 3, we tested the feasibility of automated detection of regional WM abnormalities in 11 p

93 emiautomated, dynamic measurement of LVV and automated detection of regional WM abnormalities.

94 Deep learning-enabled automated detection of RPD presence from FAF images achi

95 velopment of tools and gadgets useful in the automated detection of rust disease required for precisi

96 Automated detection of SDoH may be instrumental for heal

97 in virions and their fixed 1:1 ratio enabled automated detection of single-particle fusion in both fi

98 h manual and automated techniques, including automated detection of slow waves and eye movements.

99 The automated detection of social avoidance allows a marked

100 Automated detection of specific cells in three-dimension

101 based method for accurate classification and automated detection of spontaneous synaptic events.

102 Automated detection of stress-induced wall motion abnorm

103 neration was shown to very effective for the automated detection of structurally related nonribosomal

104 tion offers an attractive technology for the automated detection of such species.

105 Here, we report SynEM, a method for automated detection of synapses from conventionally en-b

106 n automated neuron reconstruction as well as automated detection of synapses.

107 findings have important implications for the automated detection of the disc margin and estimates of

108 al rating scores were highly correlated with automated detection of total burden volume (r = 0.58, P

109 ng a scalable and efficient solution for the automated detection of wildlife vocalizations.

110 lenge of addressing hate speech and the role automated detection plays in solving it.

111 s correlation coefficients (ICC) between the automated detection software and Observers #1 and #2 wer

112 , totaling 35,033 days, were processed using automated detection software and screened for each speci

113 and 309.21 +/- 40.98 mum, as computed by the automated detection software and the human operators, re

114 Two independent operators and an automated detection software examined corneal OCTs of 25

115 egrates RegNetZ and the Swin-Transformer for automated detection, subtype classification, and prognos

116 Therefore, it is crucial to develop an automated detection system that can instantly identify w

117 he highly sensitive electrochemiluminescence automated detection system.

118 Despite the implementation of automated detection systems and previous efficiencies, i

119 ic errors, both by medical professionals and automated detection systems.

120 r without seizure), using semi-automated and automated detection techniques.

121 enemies, there is an urgent need to develop automated-detection technologies for their conservation.

122 cal pathways can guide development of a semi-automated detection tool to surveil for CIED infection.

123 disconnect can have implications for whether automated detection tools are accepted or adopted.

124 both visual counting under a microscope and automated detection using a chip-based flow cytometer.

125 Age-related macular degeneration automated detection was applied to a 2-class classificat

126 ent of this assay reflects the potential for automated detection with rapid and reliable assaying and