Towards finding the lost generation of autistic adults: A deep and multi-view learning approach on social media

Artificial intelligence (AI) is poised to broadly reshape medicine, potentially improving the experiences of both clinicians and patients. We discuss key findings from a 2-year weekly effort to track and share key developments in medical AI. We cover prospective studies and advances in medical image analysis, which have reduced the gap between research and deployment. We also address several promising avenues for novel medical AI research, including non-image data sources, unconventional problem formulations and human-AI collaboration. Finally, we consider serious technical and ethical challenges in issues spanning from data scarcity to racial bias. As these challenges are addressed, AI's potential may be realized, making healthcare more accurate, efficient and accessible for patients worldwide.

Prevalence estimates of autism are essential for informing public policy, raising awareness, and developing research priorities. Using a systematic review, we synthesized estimates of the prevalence of autism worldwide. We examined factors accounting for variability in estimates and critically reviewed evidence relevant for hypotheses about biological or social determinants (viz., biological sex, sociodemographic status, ethnicity/race, and nativity) potentially modifying prevalence estimates of autism. We performed the search in November 2021 within Medline for studies estimating autism prevalence, published since our last systematic review in 2012. Data were extracted by two independent researchers. Since 2012, 99 estimates from 71 studies were published indicating a global autism prevalence that ranges within and across regions, with a median prevalence of 100/10,000 (range: 1.09/10,000 to 436.0/10,000). The median male‐to‐female ratio was 4.2. The median percentage of autism cases with co‐occurring intellectual disability was 33.0%. Estimates varied, likely reflecting complex and dynamic interactions between patterns of community awareness, service capacity, help seeking, and sociodemographic factors. A limitation of this review is that synthesizing methodological features precludes a quality appraisal of studies. Our findings reveal an increase in measured autism prevalence globally, reflecting the combined effects of multiple factors including the increase in community awareness and public health response globally, progress in case identification and definition, and an increase in community capacity. Hypotheses linking factors that increase the likelihood of developing autism with variations in prevalence will require research with large, representative samples and comparable autism diagnostic criteria and case‐finding methods in diverse world regions over time. Lay Summary We reviewed studies of the prevalence of autism worldwide, considering the impact of geographic, ethnic, and socioeconomic factors on prevalence estimates. Approximately 1/100 children are diagnosed with autism spectrum disorder around the world. Prevalence estimates increased over time and varied greatly within and across sociodemographic groups. These findings reflect changes in the definition of autism and differences in the methodology and contexts of prevalence studies.

Autism spectrum conditions comprise a set of early-onset neurodevelopmental syndromes with a prevalence of 1% across all ages. First diagnosis in adulthood has finally become recognised as an important clinical issue due to the increasing awareness of autism, broadening of diagnostic criteria, and the introduction of the spectrum concept. Thus, the idea of a lost generation of people who were previously excluded from a diagnosis of classic autism has arisen. Making a first diagnosis of autism spectrum conditions in adults can be challenging for practical reasons (eg, no person to provide a developmental history), developmental reasons (eg, the acquisition of learnt or camouflaging strategies), and clinical reasons (eg, high frequency of co-occurring disorders). The diagnostic process includes referral, screening, interviews with informants and patients, and functional assessments. In delineating differential diagnoses, true comorbidities, and overlapping behaviour with other psychiatric diagnoses, particular attention should be paid to anxiety, depression, obsessive-compulsive disorder, psychosis, personality disorders, and other neurodevelopmental disorders. Possible misdiagnosis, especially in women, should be explored. The creation of supportive, accepting, and autism-friendly social and physical environments is important and requires a coordinated effort across agencies and needs support from government policies.