ライフサイエンスコーパス: mobile phone

1 that provides service to collect data using mobile phones).

2 ers and nonusers (owning only old-technology mobile phones).

3 ne during clinic visits, home visits, and by mobile phone.

4 he readout can be done by a common hand-hold mobile phone.

5 ety resulting from being without access to a mobile phone.

6 ares with the adsorbed dye were taken with a mobile phone.

7 ental health care, yet most have access to a mobile phone.

8 portable, and can transfer test results via mobile phone.

9 pants to answer the mRS questionnaire in the mobile phones.

10 a mobile phone application in their personal mobile phones.

11 ovement in nurse/surgeon communication using mobile phones.

12 exposures in the head of users of hand-held mobile phones.

13 The application also functions on mobile phones.

14 d by analyzing aggregated mobility data from mobile phones.

15 vironmental monitoring and motion sensors in mobile phones.

16 (over $70 M USD unrecovered in computers and mobile phones, 2006-2014) due to operations that fail to

17 d weekly personalised text messages to their mobile phones about diet quality and physical activity f

18 As mobile phone access continues to expand globally, opport

19 ntly higher levels of education, wealth, and mobile phone access.

20 Overall, our findings suggest that boosting mobile-phone access and coverage and closing digital div

21 analyses covering 200+ countries reveal that mobile-phone access is associated with lower gender ineq

22 By emphasizing the mediating roles of mobile phone addiction and sport commitment, our finding

23 uld take into account the mediating roles of mobile phone addiction and sport commitment.

24 tion testing (mobiNAAT) platform utilizing a mobile phone and droplet magnetofluidics to deliver NAAT

25 Using both mobile phone and GPS data, we discover the existence of

26 years) initiating ART (<30 days) who owned a mobile phone and had no plans to transfer to another fac

27 ey typically use the communication between a mobile phone and its nearest antenna tower to infer posi

28 d to MW pulsed signals from GSM900/UMTS test-mobile phone and ROS, apoptosis, DNA damage, and PFG wer

29 that allows monetary value to be stored on a mobile phone and sent to other users via text messages,

30 t was largely consistent with estimates from mobile phone and travel history data.

31 ictive use trajectories for social media and mobile phones and 2 for video games.

32 des (OLEDs) are in widespread use in today's mobile phones and are likely to drive the next generatio

33 tributions of commuting fluxes per link from mobile phones and census sources are similar and highly

34 g with the availability of data derived from mobile phones and other dynamic data sources.

35 y of 0.5 Ah and realize the power supply for mobile phones and other electronic devices.

36 ward trips, and backward slips-while wearing mobile phones and previously validated, dedicated accele

37 le direct communication and powering between mobile phones and printed e-tags.

38 Here, we quantify participant activity using mobile phones and relate activity measured during real w

39 we discuss recent developments on the use of mobile phones and similar devices for biosensing applica

40 wenty-first century with the introduction of mobile phones and smartphones.

41 Here, we analyzed data generated by mobile phones and social media to estimate the weekly is

42 n, reducing the limit of detection (LOD) for mobile phones and webcams from 1000 nM to 10nM.

43 Addictive use of social media, mobile phones, and video games using validated child-rep

44 A mobile phone app (Allergy Diary, Google Play Store and A

45 A mobile phone app (Allergy Diary, which is freely availab

46 A mobile phone app (the Allergy Diary) central to MASK is

47 A mobile phone app records proximity events between app us

48 ed to 5,268 users of the iRecord Butterflies mobile phone app, a multi-species environmental citizen

49 hart, -0.12 (95% CI, -0.15 to -0.09) for the mobile phone app, and -0.13 (95% CI, -0.16 to -0.10) for

50 n was created and presented in the form of a mobile phone app.

51 A mobile phone "app" was also capable of reading the test

52 Using a specifically designed mobile phone application 'Wingtags', we collected over >

53 childhood obesity and integrate them into a mobile phone application (App).

54 Three months after inclusion, the mobile phone application automatically prompted the stud

55 lesions by community health workers using a mobile phone application compared with diagnosis by trai

56 The mobile phone application contained a set of 20 questions

57 ients and/or caregivers were equipped with a mobile phone application in their personal mobile phones

58 Measurements are wirelessly transferred to a mobile phone application that geo-tags the data and tran

59 We used a time-stamped-picture mobile phone application to record all food intake acros

60 n training of various lengths and frequency, mobile phone application with daily engagement, an onlin

61 ce guidelines in 2016 with a free, web-based mobile phone application, which was subsequently endorse

62 Automated LVO detection coupled with secure mobile phone application-based communication improved in

63 Mobile phone applications ("apps") are potentially an ef

64 Despite an explosion of mobile phone applications aimed at physical activity and

65 of public education campaigns, research with mobile phone applications, advanced skin imaging technol

66 tiation for treatment-eligible participants, mobile phone appointment reminders, health educational p

67 formation, further show that women who own a mobile phone are better informed about sexual and reprod

68 , we demonstrate that commercially available mobile phones are a powerful tool for acoustically mappi

69 provides empirical support for the idea that mobile phones are a vehicle for sustainable development

70 Mobile phones are vectors of microbes and can contribute

71 h) interventions, which require ownership of mobile phones, are being investigated throughout Africa.

72 ion and communication technology, especially mobile phones, are nearly equal in magnitude to the mean

73 The results show good use of a mobile phone as an analytical instrument.

74 A majority (61.8%) of participants owned a mobile phone at some point from 2010 to 2020.

75 equency electromagnetic fields (RF-EMF) from mobile-phone base stations and the development of nonspe

76 We modeled far-field RF-EMF exposure from mobile-phone base stations at the home addresses of the

77 In contrast to modeled RF-EMF exposure from mobile-phone base stations, perceived exposure was assoc

78 Our mobile phone based occupancy estimates are integrated wi

79 , we propose and demonstrate a new miniature mobile phone based system for ELISA (MELISA).

80 ensity, radiation based on travel times, and mobile-phone based).

81 Mobile phone-based automatic assessments of mRS performe

82 168,295 for the same period, a 5% decrease; mobile phone-based estimates predict a loss of 235,375 f

83 Mobile phone-based health interventions (mHealth) have b

84 We find that mobile phone-based mobility estimates predict the geogra

85 We therefore developed a point-of-care mobile phone-based platform that can quickly characteriz

86 terventions that incorporate traditional and mobile-phone-based education will help create smoke-free

87 roscope in combination with a cost-effective mobile-phone-based microscope can generate color images

88 it on-site diagnostics with a cost-effective mobile-phone-based multimodal microscope.

89 ascertain the most cost-effective method of mobile-phone-based reminder.

90 Mobile-phone-based reminders of scheduled HIV appointmen

91 Mobile-phone-based smoking cessation intervention has be

92 In this manuscript, we describe a mobile-phone-based strategy for real-time imaging of bip

93 addictive use trajectory for social media or mobile phones beginning at age 11 years.

94 c ways to capture human mobility measured by mobile phones; both severely overestimate the spatial sp

95 from a mixture of metals typically found in mobile phones by extraction into toluene from an aqueous

96 Mobile phone call data provide a new, first-order source

97 igital data sources, such as medical claims, mobile phone call data records, and geographically tagge

98 elop a metapopulation model parameterized by mobile phone call detail record data to estimate parasit

99 phone call, or concomitant text message and mobile phone call increase attendance at medical appoint

100 eys, (ii) proxy mobility data extracted from mobile phone call records, and (iii) the radiation model

101 er reminders sent to carers by text message, mobile phone call, or concomitant text message and mobil

102 ere, we measure behavior change reflected in mobile-phone call-detail records (CDRs), a source of pas

103 -scale data analysis techniques to study the mobile phone calling activity of people in large cities

104 The recent emergence of mobile phone calling data and associated locational info

105 ical model integrating the travel survey and mobile phone calling data.

106 nactivity periods in the people's aggregated mobile phone calling patterns and infer these to represe

107 Using mobility data inferred from mobile-phone calling records in Namibia, we calculated b

108 we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in t

109 the head not being exclusively used for all mobile phone calls, the results were similar.

110 ntific collaborations, Twitter mentions, and mobile phone calls.

111 t samples using a spotting automatic system, mobile phone camera and a computer with developed softwa

112 ld condenser and a 20x objective lens with a mobile phone camera to create an inexpensive, portable a

113 surements of the LFs were carried out with a mobile phone camera whose imaging resolution was improve

114 ring light microscopy images captured with a mobile phone camera.

115 hat accelerometry-based technologies such as mobile phones can be used to evaluate real world activit

116 nication technology such as the Internet and mobile phones can deliver behavioral components for STD/

117 Kenya, including the broader standard use of mobile phone communication between healthcare workers an

118 In the present study we utilise a large mobile phone communication dataset containing time stamp

119 than on census commuting networks, once the mobile phone commuting network is considered in the epid

120 ances and computer devices (SACD), including mobile phones, contain significant amounts of precious m

121 ical and electronic equipment (WEEE) such as mobile phones contains a plethora of metals of which gol

122 em, the Do-It-Yourself electronic module for mobile phone control has been developed.

123 ether exposure to microwaves (MW) emitted by mobile phones could induce various biochemical markers o

124 The rapid spread of mobile phones creates potential for sustainably raising

125 fected-Recovered-Deceased dynamics with real mobile phone data accounting for the population mobility

126 ing seasonal and spatial data on travel from mobile phone data allows us to characterize seasonal flu

127 Here, we use spatially explicit mobile phone data and malaria prevalence information fro

128 Our mobility networks are derived from mobile phone data and map the hourly movements of 98 mil

129 ta as well as publicly available, anonymized mobile phone data and median household income by census

130 lly discuss the advantages and the limits of mobile phone data and potential alternatives for assessi

131 Additionally, as a general rule, the mobile phone data are not linked to demographic or socia

132 of population travel (fluxes) inferred from mobile phone data are predictive of disease transmission

133 r conditions on social relationships and how mobile phone data can be used to investigate the influen

134 We show that commuting networks from mobile phone data capture the empirical commuting patter

135 set, and the mobility fluxes extracted from mobile phone data collected in a western European countr

136 els were then re-evaluated against 5-week of mobile phone data from 2017 showing mean absolute errors

137 In this study mobile phone data from 8-weeks in 2016 was used to train

138 Here we use 11,478,484 counts of mobile phone data from individuals leaving or transiting

139 e we quantify seasonal travel patterns using mobile phone data from nearly 15 million anonymous subsc

140 n different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to

141 Mobile phone data have been proposed to monitor effectiv

142 we analyzed mobility patterns inferred from mobile phone data in four Sub-Saharan African countries

143 re, we review the different applications for mobile phone data in guiding and evaluating COVID-19 res

144 emic has heightened discussion of the use of mobile phone data in outbreak response.

145 c overestimation of commuting traffic in the mobile phone data is observed.

146 on human resting or sleeping patterns using mobile phone data of a large number of individuals.

147 Mobile phone data provide a unique source of information

148 However, predicting stress levels from mobile phone data remains a challenging task, and off-th

149 fic heterogeneities in travel estimated from mobile phone data resulted in overestimating subnational

150 Mobile phone data therefore offer a valuable previously

151 Leveraging mobile phone data to guide vector control can be relevan

152 I use anonymized mobile phone data to measure exposure to air pollution a

153 rveys, parasite genetic data, and anonymized mobile phone data to measure the spatial spread of malar

154 Here, we use mobile phone data to quantify seasonal travel and direct

155 radiation model showing higher accuracy than mobile phone data when the seed is central in the networ

156 udy real anomalous events using country-wide mobile phone data, finding that information flow during

157 of massive datasets of human behavior (e.g., mobile phone data, satellite imagery), studies on disast

158 Using massive, passively-collected mobile phone data, we introduce a novel framework to est

159 Combining data on human movement from mobile phone data-derived population fluxes with data on

160 We integrate both stylized and mobile phone data-driven mobility patterns in an agent-b

161 1.21, as observed in recent studies based on mobile phone data.

162 ources and implications of selection bias in mobile phone data.

163 cal data with mobility models generated from mobile phone data.

164 rn Namibia and estimated human mobility from mobile phone data.

165 ian refugees in Turkey inferred from massive mobile-phone data to verify this concern.

166 Here, by exploiting three different mobile phone datasets that capture simultaneously these

167 Devices included are mobile phones, desktop and laptop computers, monitors, c

168 For billions of people across the globe, mobile phones enable relatively cheap and effective comm

169 re, and social norms that encourage constant mobile phone engagement.

170 l analysis directly to "the cloud" using any mobile phone, for use in resource-limited settings.

171 ntees broad compatibility with any available mobile phone (from low-end phones to smartphones) or cel

172 ing a very simple assessment tool (VAS) on a mobile phone had the potential to answer questions previ

173 escent use of social media, video games, and mobile phones has raised concerns about potential links

174 Mechanically flexible mobile phones have been long anticipated due to the rapi

175 Mobile phones have been used to monitor mobility changes

176 Data collected from mobile phones have the potential to provide insight into

177 These results suggest that two-fluorophore mobile phone imaging may enable translating the benefits

178 in-flow detection using time domain-encoded mobile phone imaging, and (iii) the integration of on-ch

179 ders using data on mobility from a sample of mobile phones in 3,100 counties in the United States dur

180 ge-scale rabies surveillance system based on mobile phones in southern Tanzania.

181 Mobile phones, in particular, have been used extensively

182 These findings provide evidence that mobile phone intervention may be a useful tool for promo

183 ealth care facilities were randomized to the mobile phone intervention or to standard care (control).

184 Compared with the control group, mobile phone intervention was associated with significan

185 Next, we reconfigured the mobile phone into a fluorescence imager by adding a low-

186 h) optical detectors, such as those found on mobile phones, is a limiting factor for many mHealth cli

187 These rapid responses leverage billions of mobile phones, large online datasets, connected devices,

188 in the intervention group received frequent mobile phone messages compared with controls who receive

189 e 2 diabetes was lower in those who received mobile phone messages than in controls: 50 (18%) partici

190 atients were randomly assigned to either the mobile phone messaging intervention (n=271) or standard

191 mputer-generated randomisation sequence to a mobile phone messaging intervention or standard care (co

192 Mobile phone messaging is an effective and acceptable me

193 Mobile phone messaging is an inexpensive alternative way

194 We aimed to assess whether mobile phone messaging that encouraged lifestyle change

195 articipatory community mobilisation, mHealth mobile phone messaging, and usual care (control) in 96 v

196 In a mobile phone metadata dataset of more than 40k people, i

197 from nasal swab RNA that can be read with a mobile phone microscope.

198 our samples can be imaged and analysed using mobile phone microscopy, achieving a new milestone for t

199 Given the ubiquity of mobile phones, mobile health interventions offer promise

200 Mobile phones (MPs) now have an extremely high penetrati

201 Here we show that data from mobile phone networks can improve the targeting of human

202 iologists received real-time alerts to their mobile phones notifying them of possible LVO within minu

203 escribed or dispensed naloxone and who had a mobile phone number listed in the electronic health reco

204 rticipants included US adults with email and mobile phone numbers.

205 Each of the 26 mobile phones of this study was contaminated with microb

206 Mobile phones offer a means to analyse population moveme

207 We collaborated with the largest mobile phone operator in Haiti (Digicel) and analyzed th

208 Facebook 'Data for Good' and data from three mobile phone operators.

209 many fluorophores in multiple wavelengths, a mobile phone or a webcam as a detector, and capillary tu

210 handheld format that is compatible with any mobile phone or network worldwide guarantees that sophis

211 No mobile phones or identification badges were positive for

212 arly well suited to mobile devices (watches, mobile phones or tablets), which require the combination

213 ting, including for example integration with mobile phones, or exhibited the potential for such opera

214 ajectories of addictive use of social media, mobile phones, or video games were common in early adole

215 In this Ugandan cohort, mobile phone ownership increased over time, although by

216 Data from mobile phone panel surveys, with a total sample of 12,61

217 Countries with high internet and mobile phone penetration have higher representation.

218 ted CPR could be increased with the use of a mobile-phone positioning system that could instantly loc

219 A mobile-phone positioning system that was activated when

220 A mobile-phone positioning system to dispatch lay voluntee

221 The mobile-phone positioning system was activated in 667 out

222 f the modified Rankin Scale (mRS) based on a mobile phone questionnaire may serve as an alternative t

223 A Google Forms mobile phone questionnaire was emailed to nine ophthalmo

224 communication patterns in a large dataset of mobile phone records and show the existence of temporal

225 Mobile phone records can provide vast quantities of spat

226 f-reports of physical proximity deviate from mobile phone records depending on the recency and salien

227 Here, we analyze a dataset of mobile phone records of approximately 150,000 users in S

228 onnectivity can be derived from data such as mobile phone records, but it is not clear how this maps

229 ed treatment adherence support delivered via mobile phone short message system (SMS) text messages on

230 lour of the sky as well as the strength of a mobile phone signal.

231 ions data and mobility trends extracted from mobile phone signals and Google.

232 Mobile phones significantly improve access to healthcare

233 with HIV were randomly assigned (1:1:1) with mobile phone software to community-based ART initiation

234 Mobile phone STD/HIV interventions using text-messaging

235 n a nationwide cohort study, 355,701 private mobile phone subscribers in Denmark from 1987 to 1995 we

236 mobility data from approximately 40 million mobile phone subscribers.

237 resuscitation, public access defibrillation, mobile phone technologies to summon first responders, an

238 Mobile phone technology has been successful in changing

239 ements in knowledge of obesity aetiology and mobile phone technology have created the opportunity to

240 (aged 16-49 years) who could receive secure mobile phone text messages were randomly assigned (1:1:1

241 ed smoking cessation programme delivered via mobile phone text messaging on continuous abstinence, wh

242 Smoking cessation programmes delivered via mobile phone text messaging show increases in self-repor

243 pendent telephone randomisation system, to a mobile phone text messaging smoking cessation programme

244 As fomites, mobile phones that are not decontaminated may pose serio

245 Owing to the capabilities of mobile phones (their cameras, connectivity, portability,

246 Integrated with a reader device based on a mobile phone, this assay has the potential to enable rap

247 The use of a handy mobile phone to remotely control the releasing process a

248 n or her next-of-kin (NOK) trimonthly on her mobile phone to update information on her vital status.

249 ingle receiver, such as the uplink from many mobile phones to a single base station.

250 wever, novel strategies including the use of mobile phones to ease stockouts, task-shifting to commun

251 of sample size, and data collection through mobile phones to improve timeliness of reporting and all

252 microchips in modern computer systems--from mobile phones to large-scale data centres.

253 These range from web browsers in mobile phones to the most popular micro service platform

254 nd integrate multiple open data sources with mobile phone traces to compare how the different factors

255 morning peak hour obtained from billions of mobile phone traces to comprehensively analyse urban tra

256 vailable geodatabases and a large dataset of mobile phone traces.

257 while mitigation efforts are estimated from mobile phone tracking data.

258 A pedestrian's or rider's use of a mobile phone up to 1 minute before a road injury was ass

259 Here, an extensive mobile phone usage data set for Kenya was processed to e

260 systems, finding that protein functions and mobile phone usage occupy distinct regions of the phase

261 Increasingly, mobile-phone usage data are used to quantify human mobil

262 Interventions to promote balanced mobile phone use and digital well-being are recommended

263 We show that an individual's past history of mobile phone use can be used to infer his or her socioec

264 een explored through the analysis of a large mobile phone use dataset.

265 Mobile phone use in the community and in professional se

266 ne instance, observed and noted the personal mobile phone use of a visitor.

267 ch researchers evaluated the associations of mobile phone use with the risks of brain, acoustic neuro

268 However, our model used reported side of mobile phone use, which is potentially in fl uenced by r

269 the study population and did not cover past mobile phone use.

270 roma, or parotid gland tumors in relation to mobile phone use.

271 ion in the investigation of brain tumors and mobile phone use.

272 A mobile phone user interface operating in tandem with a p

273 s of a full calendar year of data for 22,696 mobile phone users (53.2 million call logs) in Lisbon, P

274 four extensive datasets covering millions of mobile phone users and urban facilities, we investigate

275 Our main analysis included 792 regular mobile phone users diagnosed with a glioma between 2000

276 l) and analyzed the movements of 1.9 million mobile phone users during the period from 42 d before, t

277 dataset of more than one million anonymized mobile phone users in Boston, Dallas, Los Angeles, and S

278 We modeled the mobility of mobile phone users in order to study the fundamental spr

279 ized call detail records of over one million mobile phone users in Portugal.

280 ata collected from more than 200K anonymized mobile phone users in Tokyo.

281 Here we use movement data of mobile phone users to show that mobility in Germany has

282 e study the trajectory of 100,000 anonymized mobile phone users whose position is tracked for a six-m

283 c and demographic information of millions of mobile phone users with their communication patterns to

284 ne the communication patterns of millions of mobile phone users, allowing us to simultaneously study

285 aging location-based data from de-identified mobile phone users, we observed that, during lockdowns r

286 ncreased skin cancer risk was observed among mobile phone users.

287 studying the mobility patterns of anonymized mobile phone users.

288 sitioning system that could instantly locate mobile-phone users and dispatch lay volunteers who were

289 te rate (PR) maps and call data records from mobile phones, using a steady-state analysis of a malari

290 s to store, send, and receive money on their mobile phone via text message.

291 A small potentiostat connected to an Android mobile phone was used to detect amoxicillin in a single-

292 om a Global System for Mobile Communications mobile phone was used to update the display.

293 Entire surfaces of 5 mobile phones were swabbed and examined for their microb

294 he presence of microbes on community derived mobile phones which in 2021, numbered in the billions in

295 US residents aged 18 to 24 years who owned a mobile phone with an active text message plan, reported

296 sted in quitting within 30 days, and owned a mobile phone with an active text message plan.

297 ng in the study area, and who had a personal mobile phone with one of two phone networks, were recrui

298 The strategy consisted of: (1) using mobile phones with multipass excitation and emission fil

299 This paper compares observational data from mobile phones with standard self-report survey data.

300 We show that even low-cost mobile phones with very basic functionality are capable