ライフサイエンスコーパス: deep

1 not been a unified set of tools that allows deep and complete RNA structure analysis, and at the sam

2 Responses were deep and durable, with most complete responders achievin

3 perficial differences from those that may be deep and enduring.

4 pyramidal and inhibitory neurons located in deep and superficial layers of GC.

5 zens' responses to COVID-19 are subject to a deep-and consequential-partisan divide.

6 a, with upper GIS endoscopy performed due to deep anemia, who underwent simultaneous cesarean section

7 r deciding which type of keratoplasty (i.e., deep anterior lamellar or penetrating) should be propose

8 f this review are a group of scientists with deep appreciation for the common aims of systems neurosc

9 Recent advances in adapting deep architectures to structured data have opened a new

10 rategies for deep soil water acquisition (WA(deep) ) are critical to a species' adaptation to drought

11 F(3)-substituted ligands to show sky-blue to deep-blue photoluminescence from charge-transfer excited

12 of disposing of spent nuclear fuel (SNF) in deep boreholes has been reinvigorated, most recently by

13 cleus, dentatorubrothalamic tract, and other deep brain nuclei cannot be clearly identified.

14 We developed a mobile deep brain recording and stimulation (Mo-DBRS) platform

15 A consensus has yet to emerge whether deep brain stimulation (DBS) for treatment-refractory ob

16 Deep brain stimulation (DBS) is a treatment option for r

17 Deep brain stimulation (DBS) is an effective treatment o

18 with advanced Parkinson's can be treated by deep brain stimulation (DBS) of the subthalamic nucleus

19 internus (GPi), another effective target for deep brain stimulation (DBS).

20 Approaches such as deep brain stimulation and treatment with levodopa-carbi

21 es of dystonia may respond differentially to deep brain stimulation of the globus pallidus pars inter

22 ndings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differ

23 mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's

24 work could bring antisense oligonucleotides, deep brain stimulation, and gene therapy into the clinic

25 ntrol over specific neural cell types in the deep brain would advance the study of nervous system fun

26 2/3) in human neocortical tissue resected in deep-brain surgery, and in mice as control.

27 viations from normal breathing which we term deep breaths and bursts.

28 map and quantify axons from thalamocortical, deep cerebellar, and cortical projection neurons, valida

29 of neck muscle fat infiltration (MFI) in the deep cervical extensor muscles (multifidus and semispina

30 The deep CNN trained with 1000 samples or more per cluster h

31 lexed in situ hybridization, immunostaining, deep confocal imaging, and staged pharmacological inhibi

32 In the first, we demonstrate deep conservation of a nucleolus gene module across very

33 n prediction by harnessing the capability of deep convolutional neural network (CNN) within a MIL fra

34 Purpose To evaluate configurations of deep convolutional neural networks (CNNs) to localize an

35 Purpose To explore the use of deep convolutional neural networks (DCNNs) to generate s

36 ssing theories proposing that neurons in the deep cortical layers represent perceptual hypotheses and

37 SARA functions as a specific marker of the deep cortical layers until the first postnatal week.

38 opallium (AId), an avian analog of mammalian deep cortical layers with involvement in motor function.

39 uencing offers the potential for consistent, deep coverage of information rich genomic regions to cha

40 l D-loops with near base-pair resolution and deep coverage, while also revealing their distribution i

41 hile holes could transfer to CuO(x) to avoid deep dehydrogenation and the overoxidation of C(2) produ

42 8 years) with >=1 vital primary molar with a deep dentin lesion (>1/2 dentin depth) were included (60

43 sily induces the bad structural stability at deep desodiation states and limited reversible capacity

44 on a radiocarbon mass balance, we show that deep-DOC is consumed along with fresh-DOC in the ASP.

45 from sample return missions or inclusions in deep Earth diamonds, a nondestructive method is preferre

46 ion can reveal distinctive insights into the deep Earth.

47 stry and physics mechanisms for the possible deep-Earth Xe reservoir.

48 hippocampus reaches both major cell types of deep entorhinal layers.

49 Here, we provide a deep exploration of sRNA variation and inheritance among

50 ving ocean model to identify an unrecognized deep flow toward the Faroe Bank Channel.

51 Then, we build a cascade deep forest classifier to infer new DTIs.

52 be managing and protecting large volumes of deep fresh groundwater.

53 s to evaluate SI changes during French fries deep-frying at 170 degrees C or 180 degrees C up to 119

54 ith significant tobacco smoke exposure using deep gene resequencing and alpha-1 antitrypsin concentra

55 ts their factorial nature - both in terms of deep hierarchies over levels of abstraction and, crucial

56 orous animal provides direct evidence of the deep history of directional behavior among amniotes and

57 cations on seismic activity and transport of deep hydrocarbon-bearing fluids.

58 the existence of hot intracluster gas, while deep imaging spectroscopy from the European Space Agency

59 This finding, with deep implications for neuroscience and theory of neural

60 oderm, as hitherto assumed based on position deep in the pharynx.

61 There were significantly more deep inner retinal dimples in the temporal group (35%) c

62 re bioelectronics is wireless power delivery deep inside the body.

63 pes of mnemonic representations has provided deep insights into memory architecture and its neural un

64 Deep insights into photo-thermo catalysis are achieved v

65 Light scattering techniques yield deep insights into the changes in size and shape.

66 the identified KIRC hub genes could provide deep insights into the molecular mechanisms of KIRC.

67 CTBs track along scars deep into the myometrium and beyond.

68 patients, as opposed to only 5% in isolated deep intraparenchymal hemorrhage not extending to cortex

69 ations can require considerable effort and a deep intuition about each species' vocal behavior.

70 e systematically profiled the performance of deep, kernel, and linear models as a function of sample

71 This study allowed a deep knowledge of the regioselectivity of the reaction,

72 We found that deep layer neurons show higher baseline firing rates (FR

73 zation of the retina, microglia contacts the deep layer of high stiffness, which coincides with micro

74 igher baseline firing rates (FRs) in GC with deep-layer inhibitory neurons displaying highest FRs at

75 itant disinhibition of auditory responses in deep-layer pyramidal neurons that is selective for behav

76 n) coupled with a heightened response in the deep layers (repetition enhancement).

77 The intermediate and deep layers of the midbrain superior colliculus (SC) are

78 As an alternative, we sought to use deep learning (DL) for LV in-silico modeling.

79 I ventilation scans from free-breathing MRI (deep learning [DL] ventilation MRI)-derived specific ven

80 Here, we report the development of a deep learning algorithm for the prediction of local gene

81 ave developed a new systems-biology-informed deep learning algorithm that incorporates the system of

82 A deep learning algorithm was used to segment all baseline

83 To this end, we develop AutoRT, a deep learning algorithm with high accuracy in retention

84 As deep learning algorithms drive the progress in protein s

85 survival prediction using a hybrid method of deep learning and machine learning.

86 o be studied at this merging superhighway of deep learning and protein structure prediction.

87 rs and a segmentation routine that leverages deep learning and sparse representations to reduce the n

88 elds from microchannel elements we utilize a deep learning approach based on a deep neural network (D

89 Here, we developed a novel deep learning approach for automated quantification of s

90 The presented deep learning approach identified known as well as novel

91 Two different deep learning approaches were tested: training from rand

92 With the development of deep learning approaches, the problem of catheter assess

93 Purpose To evaluate whether deep learning can predict enhancing lesions on MRI scans

94 Thus, deep learning can reveal the regulatory syntax predictiv

95 Our framework combing supervised deep learning classification with automated un-supervise

96 plots or quantitatively with the Gene Oracle deep learning classifier.

97 State-of-the-art deep learning for object detection is poised to improve

98 A popular deep learning framework (Keras) is applied to the proble

99 The proposed deep learning framework is effective for such task.

100 Here, we present a deep learning framework to capture pathogenic noncoding

101 Here we present an End-to-End deep learning framework, circDeep, to classify circular

102 Deep learning has become the dominant technology for pro

103 While deep learning has been applied to cell segmentation prob

104 Although deep learning has demonstrated potential for each of the

105 Recently, deep learning has unlocked unprecedented success in vari

106 Our findings suggest that deep learning has utility in the identification of ENE i

107 Classification of ACL injuries using deep learning involved use of two types of CNN, one with

108 mated detection and grading network based on deep learning is proposed to enhance reproducibility.

109 A deep learning method for localization and quantification

110 A multiscale deep learning method for traumatic hemoperitoneum quanti

111 The deep learning method identified more patients with patho

112 needed.Objectives: To develop and validate a deep learning method to improve the management of IPNs.M

113 -dimensional (3D) U-Net and a coarse-to-fine deep learning method.

114 Administration (FDA), to secure safe use of deep learning methods.

115 ng with the scripts for training and testing deep learning methods.

116 The deep learning model allowed for fully automatic and robu

117 The first deep learning model DeepMS on WGS somatic mutational pro

118 We show that the proposed deep learning model significantly outperforms a traditio

119 We propose a deep learning model, so-called CLPred, which uses a bidi

120 Herein, we report a (18)F-FDG-PET/CT-based deep learning model, which demonstrates high accuracy in

121 Various deep learning models have gained success in image analys

122 Deep learning models outperformed standard RNFL thicknes

123 idden Markov models of each smORF family and deep learning models that better generalize to smORF fam

124 Deep learning models were compared with mean RNFL thickn

125 Deep learning models were pretrained on glioblastoma MRI

126 Deep learning models were trained to use SD OCT retinal

127 enome-wide SNP annotations from two previous deep learning models, DeepSEA and Basenji, by applying s

128 Although applications of deep learning networks to real-world problems have becom

129 The deep learning ranking model outperforms other approaches

130 iew highlights several needs in the field of deep learning research including use of internal dataset

131 Previous deep learning studies on optical coherence tomography (O

132 Deep learning successfully identified ENE on pretreatmen

133 d surgical workflow recognition and report a deep learning system, that not only detects surgical pha

134 ning methods have been proposed, including a deep learning technique which is sequence-based that has

135 We tested several recent deep learning techniques including wide residual network

136 without sacrificing diagnostic quality using deep learning techniques.

137 use of label-free imaging flow cytometry and deep learning to characterize RBC lesions.

138 MARS uses deep learning to learn a cell embedding function as well

139 t application of artificial intelligence and deep learning to medical image translation, by employing

140 re extraction and, integrated with CNN-based deep learning, can boost the predictive accuracy.

141 ionary potential of combined traditional and deep learning-assisted analytical approaches to overcome

142 e sequence data, we developed MapPred, a new deep learning-based contact prediction method.

143 Here we establish DeepTetrad, a deep learning-based image recognition package for pollen

144 Here, we describe OpenMonkeyStudio, a deep learning-based markerless motion capture system for

145 A specific class of deep learning-based methods allows for the prediction of

146 tly packed is a major bottleneck in standard deep learning-based models.

147 We propose DeepCleave, the first deep learning-based predictor of protease-specific subst

148 Deep learning-corrected PET (PET(DL)) images were quanti

149 lar pressure values were calculated from the deep learning-predicted tonometer and mire diameters usi

150 Such challenges can be well addressed by deep learning.

151 age advances in earthquake monitoring with a deep-learning algorithm to image a fault zone hosting a

152 machine interactions for the construction of deep-learning algorithms that benefit from expert knowle

153 We show that deep-learning architectures are capable of producing fal

154 Among other advances, deep-learning machine learning methods, including convol

155 t, overcoming the intelligibility problem of deep-learning methods.

156 We developed a deep-learning system that detects colorectal cancer spec

157 emonstrate the co-existence of both free and deep-level crumpled excitons with some traces of defect-

158 is work, we apply impedance spectroscopy and deep-level transient spectroscopy to characterize the io

159 rbon-bearing reservoir in slabs subducted to deep-lithospheric and transition-zone depths (less than

160 the Late Holocene could then have reinforced deep mixing along and across density surfaces, thus enha

161 that together show increased Si supply from deep mixing during the deglaciation with a maximum durin

162 For patients with deep molecular responses, up to half have been able to d

163 study by Ahadi et al. used longitudinal and deep multi-omic profiling to identify individuals with d

164 The deep mutational scan scores identified 40 putative gain-

165 In this study, we combined two recent deep mutational scanning (DMS) datasets probing the effe

166 Using deep mutational scanning, we engineered yeast with all 4

167 by combining a competitive growth assay with deep mutational scanning.

168 gated microwave catheter ablation can create deep myocardial lesions endocardially and epicardially t

169 The recent revelation of exceptionally deep nesting in lizards under extreme dry conditions und

170 Overparametrized deep networks predict well, despite the lack of an expli

171 learning models including random forests and deep neural nets.

172 utilize a deep learning approach based on a deep neural network (DNN) that is trained on images of p

173 hly lithiated phase of Li(7) Ti(5) O(12) for Deep Neural Network applications is reported, given the

174 ing sequential and pairwise features using a deep neural network composed of both 1 D and 2 D convolu

175 We propose a deep neural network for predicting essential genes in mi

176 We evaluate the use of a deep neural network for the detection of endoleak on CTA

177 We propose a deep neural network tensor factorization method, Avocado

178 s and Methods In this retrospective study, a deep neural network, CV19-Net, was trained, validated, a

179 Here, we investigate Deep Neural Networks (DNN) to predict toehold switch fun

180 Deep neural networks (DNNs) have achieved state-of-the-a

181 The resulting images were used to train deep neural networks for assessment of prostate biopsies

182 Deep neural networks have achieved state of the art perf

183 Deep neural networks have advanced the field of detectio

184 n capacity improves along the hierarchies of deep neural networks with different architectures.

185 including a gradient boosting model and two deep neural networks.

186 This DNA was subjected to deep next-generation sequencing and tested against a cus

187 We show that the effect of subduction on the deep nitrogen cycle may be less important than has been

188 rest neighbours by hundreds of kilometres of deep ocean and the Antarctic Circumpolar Current.

189 e a concentration threshold that buffers the deep ocean iron inventory.

190 e introduce a method that infers basin-scale deep-ocean temperature changes from the travel times of

191 and adaptations of fungal communities in the deep oceanic crust from ~10 to 780 mbsf by combining met

192 We suggest that the deep Pacific is a site of respired carbon storage associ

193 mechanism for the vertical redistribution of deep, permafrost-derived nutrients, which may alleviate

194 This cellular atlas, combined with deep-phenotypic, spatial and functional analyses of syno

195 ) indicated that the elephants were not from deep rainforests but from savanna and mixed habitats.

196 ticle discusses SORS and related variants of deep Raman spectroscopy such as transmission Raman spect

197 e conceptually demonstrate the capability of deep Raman spectroscopy to noninvasively monitor changes

198 these pathways is shown to be influenced by deep-reaching eddies and meanders of the North Atlantic

199 om complex 3D spirals and vaginal folds with deep recesses, which may curtail the depth or direction

200 latform for rapid phage display screening of deep recombinant libraries consisting of as few as one m

201 esses this unmet need through establishing a deep recurrent model to predict and eliminate the PHT co

202 rC)] (2) has been found to be an exceptional deep red (lambda(max) = 621 nm, = 0.32, tau(av) = 366 ns

203 have profound neuroscientific implications: deep reinforcement learning (RL).

204 Venetoclax is highly active at achieving deep remission for most treated patients with CLL, inclu

205 acement than the central faculae because the deep reservoir brines took a longer path to the surface

206 This work proposes DeepH3, a deep residual neural network that learns to predict inte

207 Our method first employs stacked deep ResNets to perform residue-level ensemble error cla

208 of mice, C57BL/6J and BALB/cJ, and deploying deep RNA-Seq complemented with quantitative RT-PCR, we f

209 Deep RNA-seq revealed a significant derepression of the

210 pacity to compute models of other agents has deep roots in the strategic social behavior of primates

211 poch of Madagascar that possesses a long and deep rostrum, an expression of beak morphology that was

212 d inhibitory neurons of the intermediate and deep SC.

213 In much of the deep sea (>200 m water depth), the export of nutrients f

214 eviously unobserved level of dynamism in the deep sea, potentially mirroring the great migrations so

215 ting significantly to chemical fluxes in the deep sea, yet little is known about the microbial commun

216 uct the first systematic characterization of deep-sea benthic invertebrate communities of the Galapag

217 are known to supply oxygen and nutrients to deep-sea benthos, suggesting that deep-sea biodiversity

218 Climate drivers will alter deep-sea biodiversity and associated ecosystem services,

219 trients to deep-sea benthos, suggesting that deep-sea biodiversity hotspots are also likely to be mic

220 vidence for seasonally recurring patterns in deep-sea demersal fish abundances over a 7-year period,

221 Understanding life history strategies in deep-sea environments is lacking for many species of fis

222 cold-water coral and commercially important deep-sea fish species under present-day (1951-2000) envi

223 ck skin (reflectance <0.5%) in 16 species of deep-sea fishes across seven distantly related orders.

224 delta(18)O record for global ice volume and deep-sea temperature variations.

225 To illustrate this approach, we focus on deep-seabed mining and the International Seabed Authorit

226 taminants of the marine environment, and the deep seafloor is their ultimate sink compartment.

227 Deep Sequence achieved high performance for the predicti

228 screening approach in which edited loci are deep sequenced, and candidate sites are prioritized base

229 We perform deep sequencing across the DAP1 genomic segment in 2032

230 ined with chromatin immunoprecipitation with deep sequencing and functional characterization conducte

231 Using deep sequencing approaches, we discovered that a member

232 Batch effect is a frequent challenge in deep sequencing data analysis that can lead to misleadin

233 Finally, deep sequencing illustrates DrBHV super-infections in in

234 A combination of Primer-ID and deep sequencing is a promising approach that may quantif

235 (P = 0.007).Conclusions: In this integrative deep sequencing study of SERPINA1 with alpha-1 antitryps

236 toes, polymerase chain reaction and amplicon deep sequencing were used to track species and clone-spe

237 we describe NucleaSeq-nuclease digestion and deep sequencing-a massively parallel platform that measu

238 Whole-genome deep sequencing-based analysis has revealed unexpectedly

239 ations were identified for three lines using deep sequencing-based bulked segregant analysis, and in

240 ariants more accurately compared to standard deep sequencing.

241 Deep serological profiling of 232 coronavirus disease 20

242 cks and thermodynamic modelling to show that deep serpentinization (40-80 km) generates significant a

243 Deep shotgun metagenomics unveiled distinct ecological n

244 Using deep shotgun stool metagenomics analysis, we found a rap

245 It may be caused by bacteria in deep skin structures unsusceptible to surface decontamin

246 Strategies for deep soil water acquisition (WA(deep) ) are critical to

247 nd developed a group feature selection-based deep sparse neural network model (DNN-GFS) that is optim

248 Clonality of C. acnes isolates from deep specimens from a potential periprosthetic shoulder

249 c resistance may require testing of multiple deep specimens.

250 ft when the wing is spread and operated in a deep-stall flight condition.

251 ively they generate hard-to-attain broadband deep-subwavelength absorption.

252 to quantify transverse muscle oscillations (deep-superficial displacement of the muscle boundary rel

253 nome sequencing, whole-exome sequencing, and deep targeted sequencing datasets with the NA12878 cell

254 ase-burden monitoring through the prevailing deep targeted sequencing paradigm.

255 s of morphological evolution associated with deep tetanuran divergences were more complex than curren

256 in the striatum and to assess the outcome of deep therapeutic hypothermia.

257 Among them, deep throat saliva and induced sputum are desired for RT

258 ond, that these persisting behaviors include deep tier, high-impact, complex ecosystem engineering.

259 infer patterns of brain-body co-variation in deep time.

260 the diversification of these enzymes through deep time.

261 are, in principle, considered inadequate for deep tissue stimulation unless accompanied by optic fibe

262 ad different subtypes of C. acnes within the deep tissues even though the colony morphology was simil

263 nt subtypes of C. acnes were observed in the deep tissues of a single patient.

264 t, hindering efforts to visualize targets in deep tissues.

265 Here, we perform deep transcriptomic profiling at high temporal resolutio

266 10(11) per cubic centimeter and most of the deep traps located at crystal surfaces.

267 Discovering new deep-ultraviolet (DUV) nonlinear optical (NLO) materials

268 ust decision-making framework in the face of deep uncertainties.

269 loiting the negligible cosmic-ray background deep underground at the Laboratory for Underground Nucle

270 gn and control of topology to showcase how a deep understanding of structure-property relationships c

271 oligomeric states alone does not allow for a deep understanding of the structure-function relationshi

272 However, a deep understanding of these phenomena and their redox ch

273 for high power/high temperature devices and deep-UV sensors has grown.

274 vascular complex, and microaneurysms in the deep vascular complex (DVC) (p = 0.003, 0.013, 0.028, 0.

275 -A shows less involvement of superficial and deep vascular plexus in NAION in contrast to POAG, which

276 ority of them have proximal limb-threatening deep vein thrombosis (DVT).

277 e patient (7.7%) had both cannula-associated deep vein thrombosis and pulmonary embolism.

278 there were qualitative differences such that deep vein thrombosis exclusively afflicted the immunosup

279 8%), a femoral associated cannula-associated deep vein thrombosis was identified in 10 patients (76.9

280 A jugular associated cannula-associated deep vein thrombosis was identified in seven patients (5

281 omatic venous thromboembolism was defined as deep vein thrombosis, pulmonary embolism, or both, diagn

282 ents (76.9%) had isolated cannula-associated deep vein thrombosis, two patients (15.4%) had isolated

283 both femoral and jugular cannula-associated deep vein thrombosis.

284 patient had central venous catheter-related deep vein thrombosis.

285 h acute ischemic infarct (23.3%), one with a deep venous thrombosis (1.4%), eight with multiple micro

286 t common complication was cannula-associated deep venous thrombosis (six patients, 23.1%).

287 s thromboembolism (VTE), which includes both deep venous thrombosis and pulmonary embolism, is a comm

288 Autopsy revealed deep venous thrombosis in 7 of 12 patients (58%) in whom

289 dimers were markedly higher in patients with deep venous thrombosis, both for maximum value and value

290 rombosis, thus resulting in 38.7% with PE or deep venous thrombosis, despite 40% receiving prophylact

291 tive results at CT pulmonary angiography had deep venous thrombosis, thus resulting in 38.7% with PE

292 en of 45 patients (42.2%) were found to have deep venous thrombosis.

293 -Scotland Overflow Water (ISOW) is a primary deep water mass exported from the Norwegian Sea into the

294 ethane-saturated oil droplets under emulated deep-water conditions, providing an opportunity to eluci

295 mm diameter wound (anterior), each 1-1.5 mm deep, were created on both sides of the palate.

296 sence of baseline infratentorial lesions and deep white matter lesions at 1 year.

297 cribe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model t

298 ), perovskite devices still have many states deep within the bandgap that trap charge carriers and ca

299 invade the epithelial mucus layer and reside deep within the intestinal tissue of animals.

300 livers high coulombic efficiency (ca. 97 %), deep Zn plating/stripping (10 mAh cm(-2) ), and long cyc