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A Novel Algorithm for Determining the Contextual Characteristics of Movement Behaviors by Combining Accelerometer Features and Wireless Beacons: Development and Implementation

A Novel Algorithm for Determining the Contextual Characteristics of Movement Behaviors by Combining Accelerometer Features and Wireless Beacons: Development and Implementation

We can describe this model using a transition matrix model in which the elements mi,j of the transition matrix model M are built as follows: mi,j= ai,j if i ≠ j; mi,j = 0.5 if i = j and the step counts estimates more than 2 steps in the last 10 s (a higher

Daniele Magistro, Salvatore Sessa, Andrew P Kingsnorth, Adam Loveday, Alessandro Simeone, Massimiliano Zecca, Dale W Esliger

JMIR Mhealth Uhealth 2018;6(4):e100


Training Working Memory in Adolescents Using Serious Game Elements: Pilot Randomized Controlled Trial

Training Working Memory in Adolescents Using Serious Game Elements: Pilot Randomized Controlled Trial

The standard WMC training was rated as less fun to do, Kruskal-Wallis H2)=10.093, P=.006, compared with both the gamified (Mann-Whitney’s U=233.0, z=3.145, P=.002, r=−.413) and the placebo version (U=410.5, z=2.128, P=.03, r=.301).

Wouter J Boendermaker, Thomas E Gladwin, Margot Peeters, Pier J M Prins, Reinout W Wiers

JMIR Serious Games 2018;6(2):e10


Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions

Adapting State-of-the-Art Deep Language Models to Clinical Information Extraction Systems: Potentials, Challenges, and Solutions

The training objective of the skip-gram model is to maximize the averaged log probability over all training cases (T) of appearance of the context word w_{t+j} given the current word w_t, where j is the offset of the context word from the current word in a

Liyuan Zhou, Hanna Suominen, Tom Gedeon

JMIR Med Inform 2019;7(2):e11499


Designing an Algorithm to Preserve Privacy for Medical Record Linkage With Error-Prone Data

Designing an Algorithm to Preserve Privacy for Medical Record Linkage With Error-Prone Data

To encrypt the message m, a value r ∈ Z p is randomly chosen. Then the cipher text is E(m) = (C 1, C 2)=(g r, m.h r).

Doyel Pal, Tingting Chen, Sheng Zhong, Praveen Khethavath

JMIR Med Inform 2014;2(1):e2