http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Farooq Hassan Ali (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
-
Crohn's Disease with Fistula: 10 Year Trends and Mortality in the United States
( Hassam Ali ),( Rizwan Ishtiaq ),( Muhammad Waqar Hanif ),( Rahul Pamarthy ),( Muhammad Hassan Farooq ),( Muhammad Fahd Farooq ) 대한소화기학회 2022 대한소화기학회지 Vol.80 No.3
Background/Aims: Crohn’s disease (CD) results in significant morbidity, mortality, and healthcare burden. This study evaluated the temporal trends of CD hospitalizations with a fistula over the last decade to understand the outcomes of severe CD. Methods: National Inpatient Sample database from 2009 to 2019 was used to identify CD hospitalizations with a fistula. The outcomes of interest included temporal trend analysis of length of stay (LOS), mean inpatient cost (MIC), and mortality. Results: There was an increase in the total number of fistulizing CD hospitalizations from 5,386 in 2009 to 12,900 in 2019 (p<0.01). The mean age decreased from 44.9±0.6 to 41.8±0.4 years for the study period (p<0.01). Caucasians were the predominant ethnicity, followed by Africans, Hispanics, and others (p<0.001). The mean LOS for fistulizing CD hospitalizations decreased significantly from 11.57±0.09 days in 2009 to 7.20±0.05 days in 2019 (p<0.001). There was a significant decrease in inpatient mortality from 1.72% in 2009 to 0.73% in 2019 (p<0.01). The MIC did not have a significant trend. There was a decreasing trend toward partial/total colectomies, rectosigmoid, and small bowel surgeries from 2009 to 2019 (p<0.001). Conclusions: There has been a rise in CD hospitalizations with fistulizing disease in the last decade. Despite this, the mortality and inpatient LOS have been decreasing significantly. In addition, the increase in CD hospitalizations with fistulizing disease has had no significant effect on hospital costs. (Korean J Gastroenterol 2022;80:142-148)
-
( Syed Farooq Ali ),( Malik Tahir Hassan ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.8
Most of the accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which include talking with passengers while driving, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness, fatigue and different driver’s head rotations due to change in yaw, pitch and roll angle. The contribution of this paper is two-fold. Firstly, a data set is generated for conducting different experiments on driver’s distraction. Secondly, novel approaches are presented that use features based on facial points; especially the features computed using motion vectors and interpolation to detect a special type of driver’s distraction, i.e., driver’s head rotation due to change in yaw angle. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). Various types of classifiers are trained and tested on different frames to decide about a driver's distraction. These approaches are also scale invariant. The results show that the approach that uses the novel ideas of motion vectors and interpolation outperforms other approaches in detection of driver’s head rotation. We are able to achieve a percentage accuracy of 98.45 using Neural Network.
-
Comprehensible knowledge model creation for cancer treatment decision making
Afzal, Muhammad,Hussain, Maqbool,Ali Khan, Wajahat,Ali, Taqdir,Lee, Sungyoung,Huh, Eui-Nam,Farooq Ahmad, Hafiz,Jamshed, Arif,Iqbal, Hassan,Irfan, Muhammad,Abbas Hydari, Manzar Elsevier 2017 Computers in biology and medicine Vol.82 No.-
<P><B>Abstract</B></P> <P> <I>Background</I>: A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. <I>Materials and Methods</I>: An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. With the CKM-CT, clinical data are acquired automatically from documents. Quality of data is ensured by correcting errors and transforming various formats into a standard data format. Data preprocessing involves dimensionality reduction and missing value imputation. Predictive algorithm selection is performed on the basis of the ranking score of the weighted sum model. The knowledge builder prepares knowledge for knowledge-based services: clinical decisions and education support. <I>Results</I>: Data is acquired from 13,788 head and neck cancer (HNC) documents for 3447 patients, including 1526 patients of the oral cavity site. In the data quality task, 160 staging values are corrected. In the preprocessing task, 20 attributes and 106 records are eliminated from the dataset. The Classification and Regression Trees (CRT) algorithm is selected and provides 69.0% classification accuracy in predicting HNC treatment plans, consisting of 11 decision paths that yield 11 decision rules. <I>Conclusion</I>: Our proposed methodology, CKM-CT, is helpful to find hidden knowledge in clinical documents. In CKM-CT, the prediction models are developed to assist and educate clinicians for informed decision making. The proposed methodology is generalizable to apply to data of other domains such as breast cancer with a similar objective to assist clinicians in decision making and education.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Automated methods for data acquisition from clinical documents and preprocessing. </LI> <LI> Data quality assessment and standardization of language for improved data accuracy. </LI> <LI> Machine learning algorithm selection on the basis of weighted sum model's ranking score. </LI> <LI> The development of a decision tree-based knowledge model for treatment recommendations. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
-
Ahmed Kadhim Hussein,Hameed Kadhem Hamzah,Farooq Hassan Ali,Masoud Afrand 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.4
Natural convection in an F-shaped cavity containing Ag-water non-Newtonian nanofluid (NF) saturatedwith a porous medium was investigated numerically. The left wall of the cavity was maintained at a constant hot temperatureand subjected to a horizontal periodic magnetic field. The right wall was maintained at a constant cold temperature. Both the top and bottom walls of the cavity were kept thermally insulated. In the present work, the Hartmannnumber varied as (0Ha60), the power law index varied as (0.6n1.4), the periodic shape parameter varied as(0.11), the Rayleigh number varied as (103Ra106), the aspect ratio of the cavity varied as (0.1AR0.4), theDarcy number varied as (105Da101) and the solid volume fraction varied as (0 0.06). It was found that theaverage Nusselt number (Nu) increases by increasing the (, Da and Ra), whereas it decreases when (n) and (Ha)increase. Furthermore, it was realized that the relationship between the (Nu) and () exhibits a different behaviordepending on the considered values of (Ra) and (n).
-
ScienceON연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
