Artificial intelligence is dramatically transforming medical imaging. In Saudi Arabia, there are a lack of studies assessing the level of artificial intelligence use and reliably determining the perceived impact of artificial intelligence on the radiology workflow and the profession. We assessed the levels of artificial intelligence use among radiology trainees and correlated the perceived impact of artificial intelligence on the workflow and profession with the behavioral intention to use artificial intelligence. This cross-sectional study enrolled radiology trainees from Saudi Arabia, and a 5-part-structured questionnaire was disseminated. The items concerning the perceived impact of artificial intelligence on the radiology workflow conformed to the six-step standard workflow in radiology, which includes ordering and scheduling, protocoling and acquisition, image interpretation, reporting, communication, and billing. We included 98 participants. Few used artificial intelligence in routine practice (7%). The perceived impact of artificial intelligence on the radiology workflow was at a considerable level in all radiology workflow steps (range, 3.64–3.97 out of 5). Behavioral intention to use artificial intelligence was linearly correlated with the perceptions of its impact on the radiology workflow and on the profession (p < 0.001). Artificial intelligence is used at a low level in radiology. The perceived impact of artificial intelligence on radiology workflow and the profession is correlated to an increase in behavioral intention to use artificial intelligence. Thus, increasing awareness about the positive impact of artificial intelligence can improve its adoption.

The therapeutic options of nonsmall cell lung cancer (NSCLC) therapy has been changed since the first discovery of activating epidermal growth factor receptor (EGFR) mutations and the development of specific EGFR tyrosine kinase inhibitors, which resulted in the evolution of "personalized medicine." There are a considerable number of genomic aberrations in NSCLC serving as potential predictive biomarkers and drug targets and still more. We summarized the molecular pathways, potential targets, and possible impact on disease outcome in NSCLC.

Objectives:This study aimed to describe inpatient clinical conditions at an advanced care facility in Saudi Arabia during the annual Hajj pilgrimage and to determine factors correlating with length of stay (LOS).Methods:This retrospective study was conducted at the King Abdullah Medical City (KAMC), Makkah, Saudi Arabia, and included all inpatients admitted during the annual Hajj pilgrimage between August and October 2015. Demographic, administrative and clinical data were collected from patient charts and analysed.Results:A total of 296 inpatients were included in the study, of which the majority were male (73.6%) and ≥55 years old (77%). Walk-in admissions occurred less frequently than referrals (38.9% versus 61.1%). Most patients (41.6%) were admitted during the peak Hajj period (the 8-13th days of Dhu al-Hijjah). Acute coronary syndrome was the most prevalent provisional diagnosis (65.2%). In terms of outcomes, 89.2% of the inpatients were discharged in a stable condition, with 37.5% discharged within ≤24 hours of admission. However, 39.9% required admission to the Intensive Care Unit (ICU). Overall, LOS was significantly associated with various factors, including the mode of admission, admission period, admitting department, number of comorbidities and ICU admission (P <0.050 each).Conclusion:Most of admissions were referrals, and the main Hajj period witnessed the majority of admissions. The vast majority of inpatients eventually discharged in a stable condition. Determinants of the length of hospital stay were the mode of admission, admission period, admitting department, number of comorbidities and ICU admission.

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