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1.
PLoS Comput Biol ; 18(1): e1009719, 2022 01.
Article En | MEDLINE | ID: mdl-35100256

Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The UCSF AI4ALL program was established in 2019 to address this issue by targeting high school students from underrepresented backgrounds in AI, giving them a chance to learn about AI with a focus on biomedicine, and promoting diversity and inclusion. In 2020, the UCSF AI4ALL three-week program was held entirely online due to the COVID-19 pandemic. Thus, students participated virtually to gain experience with AI, interact with diverse role models in AI, and learn about advancing health through AI. Specifically, they attended lectures in coding and AI, received an in-depth research experience through hands-on projects exploring COVID-19, and engaged in mentoring and personal development sessions with faculty, researchers, industry professionals, and undergraduate and graduate students, many of whom were women and from underrepresented racial and ethnic backgrounds. At the conclusion of the program, the students presented the results of their research projects at the final symposium. Comparison of pre- and post-program survey responses from students demonstrated that after the program, significantly more students were familiar with how to work with data and to evaluate and apply machine learning algorithms. There were also nominally significant increases in the students' knowing people in AI from historically underrepresented groups, feeling confident in discussing AI, and being aware of careers in AI. We found that we were able to engage young students in AI via our online training program and nurture greater diversity in AI. This work can guide AI training programs aspiring to engage and educate students entirely online, and motivate people in AI to strive towards increasing diversity and inclusion in this field.


Artificial Intelligence , Biomedical Research , Computational Biology , Cultural Diversity , Mentoring , Adolescent , Biomedical Research/education , Biomedical Research/organization & administration , Computational Biology/education , Computational Biology/organization & administration , Female , Humans , Male , Minority Groups , Students
2.
Br J Community Nurs ; 8(1): 24-7, 2003 Jan.
Article En | MEDLINE | ID: mdl-12574731

To determine the effectiveness of modified cow's milk formulas on the symptoms of infant colic, a mini-review (Griffiths, 2002) of double-blind randomized controlled trials was undertaken. The population was infants diagnosed with colic and the outcome was a reduction in infant distress. Medline, Embase, CINAHL and the Cochrane Library were searched and seven clinical trials and two systematic reviews were identified. After applying inclusion criteria, two studies were examined in the review. One study compared the effects of a modified formula and a standard cow's milk formula on bottle-fed infants. The other examined the effects of a low-allergen diet on breast-fed and bottle-fed infants. Results could only be retrieved from one study, which showed that hydrolysed formulas have a positive effect on reducing the symptoms of infant colic although sample sizes were small and the magnitude of benefit unclear. There is evidence to support advice to parents of bottle-fed infants with colic to consider changing to such formulas.


Colic/diet therapy , Infant Food , Milk , Animals , Cattle , Crying , Female , Humans , Infant , Randomized Controlled Trials as Topic , Treatment Outcome
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