ライフサイエンスコーパス: intelligence

1 dations for Interventional Trials-Artificial Intelligence).

2 ted Standards of Reporting Trials-Artificial Intelligence).

3 onal connectivity and behaviour (e.g., fluid intelligence).

4 main challenges in the pursuit of artificial intelligence.

5 are rapidly promoting advances in artificial intelligence.

6 red to adopt machine learning and artificial intelligence.

7 hnologies as machine learning and artificial intelligence.

8 e behavior is an enhanced form of collective intelligence.

9 referred to as the Drosophila of artificial intelligence.

10 xploring the effect of CNV burden on general intelligence.

11 how to design biological inspired artificial intelligence.

12 ciated with reduced polygenic risk score for intelligence.

13 foundational for building artificial general intelligence.

14 s a major obstacle to progress in artificial intelligence.

15 practice, ushering in a new era of surgical intelligence.

16 nsing, personalized medicare, and artificial intelligence.

17 latent variables of spatial and verbal fluid intelligence.

18 nclude artificial neurons used in Artificial Intelligence.

19 s applications, including artificial general intelligence.

20 h learning continuous theories by artificial intelligence.

21 cs, human-machine interfacing and artificial intelligence.

22 nd its role in fostering adaptive collective intelligence.

23 trait-level educational attainment and fluid intelligence.

24 ment (0.86[0.82; 0.91]; p = 2 x 10(-7)), and intelligence (0.72[0.68; 0.76]; p = 9 x 10(-29)).

25 ts receiving L-dopa improved less in spatial intelligence (-0.267 SDs; 95%CI [-0.498, -0.036]; p = 0.

26 rm for the development of artificial general intelligence(14,15).

27 ive (Wechsler Primary and Preschool Scale of Intelligence, 3rd Edition), and behavioral (Child Behavi

28 ve function reaction time (- 4.8%) and fluid intelligence accuracy (+ 19.5%)].

29 An artificial intelligence (AI) algorithm applied to electrocardiograp

30 The artificial intelligence (AI) algorithm presented here has a precisi

31 An artificial intelligence (AI) algorithm to detect COVID-19 on chest

32 In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findi

33 not well captured by widely used artificial intelligence (AI) and computational modeling frameworks.

34 tantial progress has been made in artificial intelligence (AI) and its application to medicine.

35 The emergence of artificial intelligence (AI) and its progressively wider impact on

36 Artificial intelligence (AI) and machine learning (ML) in medicine

37 combining modern technologies of artificial intelligence (AI) and microfluidics.

38 Artificial Intelligence (AI) and network methods routinely build on

39 nical data for the development of artificial intelligence (AI) applications.

40 Instead, we propose the use of artificial intelligence (AI) approaches to build a data-driven fram

41 sonance (SPR)-based biosensor and artificial intelligence (AI) assisted diagnosis of COVID-19 are emp

42 Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast int

43 Artificial intelligence (AI) continues to garner substantial intere

44 ith recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the

45 Artificial intelligence (AI) describes systems capable of making de

46 extensive reliance on cloud-based artificial intelligence (AI) for data analysis; (5) potential bias

47 Artificial intelligence (AI) has demonstrated promise in predicting

48 Artificial intelligence (AI) has numerous applications in surgical

49 Artificial intelligence (AI) has the potential to aid in rapid eval

50 Artificial intelligence (AI) has the potential to fundamentally alt

51 The latest developments in artificial intelligence (AI) have arrived into an existing state of

52 Although artificial intelligence (AI) helps to reduce the labor of reading p

53 Breakthroughs in artificial intelligence (AI) hold enormous potential as it can auto

54 Artificial intelligence (AI) holds promise for cardiovascular medic

55 Artificial intelligence (AI) is a technology that utilizes machines

56 Artificial intelligence (AI) is becoming established in drug discov

57 Artificial intelligence (AI) is becoming increasingly present in ra

58 The emergence of powerful artificial intelligence (AI) is defining new research directions in

59 As artificial intelligence (AI) is increasingly applied to biomedical

60 Artificial intelligence (AI) is increasingly becoming an important

61 Advanced artificial intelligence (AI) methods in high-resolution retinal ima

62 es (LMICs) have raised hopes that artificial intelligence (AI) might help to address challenges uniqu

63 tion that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective

64 tion that interventions involving artificial intelligence (AI) need to undergo rigorous, prospective

65 nces in machine learning (ML) and artificial intelligence (AI) present an opportunity to build better

66 An artificial intelligence (AI) program, consisting of recurrent netwo

67 r will encounter the Big data and Artificial Intelligence (AI) revolution.

68 Background Although artificial intelligence (AI) shows promise across many aspects of r

69 To evaluate the performance of an artificial intelligence (AI) system for detection of COVID-19 pneum

70 Here we present an artificial intelligence (AI) system that is capable of surpassing h

71 exAMD in one eye, we introduce an artificial intelligence (AI) system to predict progression to exAMD

72 The performance of the artificial intelligence (AI) system was assessed by comparing diagn

73 s (ICCs) for the radiologists and artificial intelligence (AI) system were calculated on a subset of

74 problems, we aimed to develop an artificial intelligence (AI) system with clinically acceptable accu

75 As artificial intelligence (AI) systems begin to make their way into c

76 Artificial intelligence (AI) systems for computer-aided diagnosis a

77 ncreasing number of automated and artificial intelligence (AI) systems make medical treatment recomme

78 Artificial intelligence (AI) tools are increasingly being applied i

79 diseases, either visually or with artificial intelligence (AI), allows radiologists to improve diagno

80 Significant advances in artificial intelligence (AI), deep learning, and other machine-lear

81 s leads us to a general sketch of artificial intelligence (AI), Searle's Chinese room, and Strevens'

82 This leads us to artificial intelligence (AI), Searle's Chinese room, and Strevens'

83 used in various fields, including artificial intelligence (AI), signal processing and bioinformatics.

84 e is great interest in developing artificial intelligence (AI)-based computer-aided detection (CAD) s

85 ER tool was derived using a novel Artificial Intelligence (AI)-methodology called optimal classificat

86 on Internet of Things (IoTs) and artificial intelligence (AI).

87 ss the theoretical performance of artificial intelligence (AI)/machine learning (ML) algorithms to au

88 question from the perspective of artificial intelligence (AI): If you have an intelligent agent that

89 using computer vision, an area of artificial intelligence aimed at interpreting images.

90 oth SCZ and BD share genetic influences with intelligence, albeit in a different manner, providing ne

91 d validated a deep learning-based artificial intelligence algorithm (DLA) for detecting MI using 6-le

92 Finally, our explainable artificial intelligence algorithm identified a mutational hotspot i

93 We evaluated a prototype artificial intelligence algorithm to classify basal lung opacities

94 Purpose To develop an artificial intelligence algorithm to differentiate COVID-19 pneumon

95 formances of radiologists and the artificial intelligence algorithm were quantified by receiver-opera

96 Conclusion DeepCOVID-XR, an artificial intelligence algorithm, detected coronavirus disease 201

97 higher results compared with the artificial intelligence algorithm: artificial intelligence-area und

98 ference between radiologist's and artificial intelligence algorithm: artificial intelligence-area und

99 The development of artificial intelligence algorithms typically demands abundant high-

100 al decision making in health, public policy, intelligence analysis, and risk management.

101 atric and neurodegenerative disorders and of intelligence and 2) testing for correlation with the pre

102 sed assessment of visual perception, general intelligence and academic achievement, using adjustments

103 and mental disorders, while NTM is linked to intelligence and cognitive function.

104 f knowledge, "neat" approaches in artificial intelligence and decision theory, neo-empiricist models

105 model as the first application of artificial intelligence and deep learning to medical image translat

106 Artificial intelligence and digital slide scanning show promise for

107 ual scores for educational attainment, fluid intelligence and dimensional measures of depression, anx

108 s a multivariable Mendelian randomization of intelligence and education.

109 lly on cognitive neuroscience and artificial intelligence and exploiting query-based attention.

110 heterozygous females typically having normal intelligence and highly skewed X chromosome inactivation

111 Artificial intelligence and machine learning (AI-ML) have taken cen

112 proach used to present flags from artificial intelligence and machine learning algorithms to the radi

113 Artificial intelligence and machine learning have demonstrated thei

114 ield of predictive modeling using artificial intelligence and machine learning have the potential to

115 From artificial intelligence and machine learning perspectives, problem

116 es from software engineering with artificial intelligence and machine learning.

117 technology, digital therapeutics, artificial intelligence and machine learning.

118 D with dyspnea when analyzed with artificial intelligence and outperforms NT-proBNP.

119 gle-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease mo

120 This paper describes the combined artificial intelligence and plasma emission spectroscopy to identif

121 Artificial intelligence and radiomics have the potential to further

122 are fundamental requirements for artificial intelligence and robotics with autonomous navigation.

123 h the literature on the associations between intelligence and schooling and early linear growth.

124 ations between growth from birth to 18 y and intelligence and schooling in a cohort.

125 hat adolescent growth is not associated with intelligence and schooling, and are consistent with the

126 ers discussed the capabilities of artificial intelligence and the potential for use of machine learni

127 Artificial intelligence and/or machine learning was applied to many

128 ct genomic loci associated with both SCZ and intelligence, and 12 loci associated with both BD and in

129 ngthen recent assessments of ravens' general intelligence, and aid to the growing evidence that the l

130 ygenic scores, derived for schizophrenia and intelligence, and evaluated their use for individual ris

131 mand' (MD) system is closely linked to fluid intelligence, and recent imaging data define nine specif

132 controlling for psychomotor vigilance, fluid intelligence, and self-reported desirability to behave i

133 I argue that we can understand human intelligence, and the ways in which it may differ from a

134 d likelihood of schizophrenia-independent of intelligence-and, hence, may be entangled with the healt

135 Artificial intelligence applied to electrocardiography has yielded

136 was to evaluate a fully automated artificial intelligence approach for predicting the status of sever

137 This study sought to develop an artificial intelligence approach for the detection of HCM based on

138 guage processing techniques as an artificial intelligence approach have been leveraged to extract inf

139 We developed an artificial intelligence approach to recognize off-sample ion images

140 A brief overview of artificial intelligence approaches and algorithms is presented, and

141 Artificial intelligence approaches are beginning to have considerab

142 These studies demonstrate that artificial intelligence approaches combined with imaging can have c

143 Overall, our work illustrates how artificial intelligence approaches enabled by open-access data, web

144 les in which machine learning and artificial intelligence are already in use in health care and appea

145 Education and intelligence are highly correlated and inversely associa

146 vironmental risk factors and with artificial intelligence are needed.

147 Phenotypes such as height and intelligence, are thought to be a product of the collect

148 rtificial intelligence algorithm: artificial intelligence-area under the receiver-operating character

149 rtificial intelligence algorithm: artificial intelligence-area under the receiver-operating character

150 rithm and radiologists, we regard artificial intelligence as a promising clinical decision support to

151 es is to accurately explain domains of human intelligence as executable, neurally mechanistic models.

152 unique opportunity for the use of artificial intelligence assistance systems to alleviate the workloa

153 We hypothesized that artificial intelligence-assisted nonmydriatic point-of-care screeni

154 e number of missed findings in an artificial intelligence-assisted reading setting.

155 s in FT children, was associated with higher intelligence at 13 years.

156 nce, and 12 loci associated with both BD and intelligence at conjunctional FDR < 0.01.

157 zed image analysis and the use of artificial intelligence-based approaches for image-based analysis a

158 ical imaging modalities and novel artificial intelligence-based approaches, as well as to evaluate th

159 djustments guided by an automated artificial intelligence-based decision support system (AI-DSS) is a

160 Artificial intelligence-based detection achieved a higher level of

161 eful adjunct to human-focused and artificial intelligence-based forms of research in order to improve

162 Here, a hybrid artificial-intelligence-based framework consolidating compositional

163 dological issues in evaluation of artificial intelligence-based interventions, reporting standards to

164 This artificial-intelligence-based material characterization approach is

165 The CADe system included an artificial intelligence-based medical device (GI-Genius, Medtronic)

166 We examined whether an artificial intelligence-based method could estimate TMTV with a com

167 We report a new Artificial Intelligence-based protein structure Refinement method c

168 enetic variants linked to higher SES, higher intelligence, better self-rated health, and longer life.

169 pooling, translating to greater 'collective intelligence', but face increased coordination challenge

170 Language is crucial for human intelligence, but what exactly is its role?

171 ways in which it may differ from artificial intelligence, by considering the characteristics of the

172 tions but also how this branch of artificial intelligence can be used to advance this exciting resear

173 This study shows that artificial intelligence can help refine the prediction of HCC progn

174 We discuss how combining human and machine intelligence can raise confidence in research, provide r

175 , bringing efficient and low-cost artificial intelligence close to the end user and Internet-of-Thing

176 n ADHD and educational attainment or general intelligence (conjunctional FDR < 0.01) and 46 were nove

177 In daily living spaces, ambient intelligence could prolong the independence of older ind

178 Longitudinal intelligence data from 79 patients (37 PRT, 42 XRT) were

179 ative bright-field microscopy and artificial intelligence (deep neural networks and traditional machi

180 95% CI: 11.06, 12.97; P < .0001) artificial intelligence-detected ICH examinations with reprioritiza

181 likelihood of schizophrenia, whereas higher intelligence distinctly and independently decreases it.

182 , a natural language-oriented and artificial intelligence-driven analytics platform, enables the broa

183 rapid progress in the development of robotic intelligence, electronic skin, wearable health as well a

184 trospectively applied a validated artificial intelligence-enabled ECG algorithm for the identificatio

185 The artificial intelligence-enabled ECG algorithm identified LVSD with

186 was to assess the accuracy of an artificial intelligence-enabled ECG to identify patients presenting

187 Groups high in both forms of intelligence engage in more effective collective action

188 For intelligence evolution, it is found that a rare-intellig

189 iders, arguing these select for 'Napoleonic' intelligence; explain potential influences on the SIH; a

190 ted Standards of Reporting Trials-Artificial Intelligence) extension is a new reporting guideline for

191 dations for Interventional Trials-Artificial Intelligence) extension is a new reporting guideline for

192 With those intelligence features, the new generation of SPR-intelli

193 es of heterogeneity: sex, age and full-scale intelligence (FIQ).

194 d about the power of visual imagery in human intelligence, from how Nobel prize-winning physicists ma

195 General cognitive ability, or general intelligence (g), is central to cognitive science, yet t

196 is forms the basis for the general factor of intelligence (g).

197 teraction in the clinical setting, augmented intelligence has been proposed as a cognitive extension

198 Artificial intelligence has recently made a disruptive impact in me

199 on the role of social networks in collective intelligence have overlooked the dynamic nature of socia

200 analysis of the loci shared between SCZ and intelligence implicated biological processes related to

201 inct cognitive abilities, general and social intelligence, improve the ability of groups to manage a

202 oauthor network from the field of artificial intelligence in education, an emerging interdisciplinary

203 All images were uploaded to the Intelligence in Medical Technologies database directly f

204 ools to ensure responsible use of artificial intelligence in medicine.

205 ill be critical to the success of artificial intelligence in radiology.

206 SCZ and BD conditional on associations with intelligence indicating polygenic overlap.

207 Artificial intelligence inference, however, especially for visual c

208 n after accounting for measures of childhood intelligence (IQ), negative affect, and prior mental hea

209 he selection effect that if the evolution of intelligence is a slow process, then life's early start

210 Artificial intelligence is becoming increasingly important in derma

211 Artificial intelligence is increasingly being used to improve diagn

212 An important aspect of intelligence is the ability to adapt to a novel task wit

213 Machine learning, a subfield of artificial intelligence, is enabling scientists, clinicians and pat

214 Instead of bolstering collective intelligence, it relies on competition between proprieta

215 ess this challenge, we developed the Machine Intelligence Learning Optimizer (MILO), an automated mac

216 ight and dementia and explored the impact of intelligence level, educational attainment, early life e

217 netic risk of coronary artery disease, lower intelligence, lower socioeconomic status (SES), and poor

218 ortex and insights into autonomy and general intelligence may be found in other brain regions that ar

219 cally favor life to frequently reemerge, but intelligence may not be as inevitable.

220 this study we investigate how computational intelligence methods can be applied to predict novel the

221 re recently, machine learning and artificial intelligence methods in chemical sciences.

222 r profiling, biomedical big data and machine intelligence methods will augment the treatment and prev

223 cult to develop a mathematical or artificial intelligence model that describes the time evolution of

224 Here, we trained an artificial intelligence model to estimate a paper's replicability u

225 Our arrangement can be embedded in an Intelligence Module that can classify sensorgrams and id

226 alth, researchers in the field of artificial intelligence must become actively anti-racist.

227 Z (n = 82,315), BD (n = 51,710), and general intelligence (n = 269,867) to investigate overlap in com

228 tional attainment (N = 842,499), and general intelligence (N = 269,867) using a conditional/conjuncti

229 hic lateral sclerosis, depression, insomnia, intelligence, neuroticism, and schizophrenia).

230 Artificial intelligence offers promising solutions for property pre

231 lopments, including the impact of artificial intelligence on the field of OA imaging, will also be di

232 underlie individual differences in childhood intelligence, particularly in high risk populations.

233 ntactless sensors have given rise to ambient intelligence-physical spaces that are sensitive and resp

234 This study introduces an Augmented Intelligence platform for the real-time synthesis of ins

235 asured automatically inline using artificial intelligence quantification of cardiovascular magnetic r

236 between institutionalization and both lower intelligence quotient (IQ) and higher levels of attentio

237 rrelates of prenatal and postnatal growth on Intelligence Quotient (IQ) in childhood in term-born chi

238 nditional length >=1 z score at 1 y had mean intelligence quotient (IQ) scores at 18 y 4.50 points (9

239 Intelligence quotient (IQ) was significantly lower in pa

240 es of cognitive impairments [e.g., decreased intelligence quotient (IQ), academic performance] and ne

241 ibited superior long-term outcomes in global intelligence quotient (IQ), perceptual reasoning, and wo

242 rajectories between groups in the domains of intelligence quotient (IQ), processing speed, working me

243 y associated with schizophrenia and baseline intelligence quotient (IQ), respectively, but schizophre

244 sed brain connectivity correlates with lower intelligence quotients (IQ) in individuals with DS; howe

245 the efficacy of an approach from artificial intelligence-reinforcement learning-for the control of c

246 st coherent, while psychiatric disorders and intelligence-related traits were the least coherent.

247 hes to biomimetic or neuromorphic artificial intelligence rely on elaborate transistor circuits to si

248 theory of dopamine, imported from artificial intelligence, represents the full distribution over futu

249 Artificial intelligence research has seen enormous progress over th

250 advances in machine learning and artificial intelligence research have opened up new ways of thinkin

251 ement learning inspired by recent artificial intelligence research on distributional reinforcement le

252 ave long been used as testbeds in artificial intelligence research, aptly referred to as the Drosophi

253 the Wechsler Primary and Preschool Scales of Intelligence-Revised.

254 assessed objectively via the Wechsler Adult Intelligence Scale IV (IQ range, 40-160, standardized to

255 The Wechsler Adult Intelligence Scale was applied at age 18 y, and primary

256 y-adjusted norms for six SIP [Wechsler-Adult-Intelligence-Scale (WAIS)-III Digit Symbol (WAIS-IIIDS)

257 elligence evolution, it is found that a rare-intelligence scenario is slightly favored at 3:2 betting

258 working memory scores (p = 0.023) and fluid intelligence scores (p = 0.033) as measured using age-st

259 is exciting time for genomics and artificial intelligence, several critical aspects of data generatio

260 playing field between natural and artificial intelligence, so that we can separate more superficial d

261 ed that these data can be used in artificial intelligence studies.

262 ny of the properties we associate with human intelligence, such as rapid learning, the ability to bre

263 c models toward explaining entire domains of intelligence, such as vision, language, and motor contro

264 Recent analyses of fluid intelligence suggest a core process of cognitive focus a

265 Conclusion An artificial intelligence system for brain MRI approached overall top

266 Conclusion Use of an artificial intelligence system improves radiologists' performance i

267 Conclusion The performance of an artificial intelligence system in the detection of coronavirus dise

268 Fundamental to artificial intelligence systems are bioinspired neuromorphic vision

269 of cutting-edge technologies, as artificial intelligence systems, is likely to shorten the reading t

270 latforms for future computing and Artificial Intelligence systems.

271 able electronics and multifaceted artificial intelligence systems.

272 bility and building more flexible artificial intelligence systems.

273 Artificial intelligence tasks across numerous applications require

274 ideo game environment for testing artificial intelligence techniques, in which model-based planning a

275 nced spatial, location-aware, and artificial intelligence technologies to investigate long-term effec

276 ons of deep learning, the leading artificial intelligence technology for image analysis, and discuss

277 We developed artificial intelligence technology that provides biomarker candidat

278 Educational attainment and intelligence test performance are heritable.

279 ndexed notably by educational attainment and intelligence test performance) constitute a central clus

280 turnout and both educational attainment and intelligence test performance.

281 e and weakened slightly after adjustment for intelligence test scores and educational level.

282 Intelligence test scores were obtained for a sample of p

283 rs of age using the Snijders-Oomen Nonverbal Intelligence Test-Revised.

284 oblems from the Raven's Progressive Matrices intelligence test.

285 measures, educational attainment, and fluid intelligence, testing them for association with dyslexia

286 sed artificial agents can solve visuospatial intelligence tests.

287 ologically inspired algorithms in artificial intelligence, the human multiple-target tracking (MTT) a

288 Then, by applying artificial intelligence, this model was used to determine optimal a

289 atural sciences, engineering, and artificial intelligence to contemporary classical and rock music.

290 Machine learning (ML) utilizes artificial intelligence to generate predictive models efficiently a

291 ill review the potential role for artificial intelligence to improve image analysis, disease diagnosi

292 drone-borne thermal imaging with artificial intelligence to locate ground-nests of birds on agricult

293 rtual clinical trials, the use of artificial intelligence to streamline and interpret data, and integ

294 , age, and sex groups for all new artificial intelligence tools to ensure responsible use of artifici

295 erging statistical, inference and artificial intelligence tools.

296 nique of deep learning, an arm of artificial intelligence, using color fundus photographs from AREDS/

297 Educational attainment and fluid intelligence were mainly negatively associated with stat

298 to achieve this goal in the domain of visual intelligence with the case study of an integrative bench

299 omputation, machine learning, and artificial intelligence work collectively to reveal the origins of

300 (DNN) and associated explainable artificial intelligence (XAI) algorithms, we show how machine learn