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DOUB's SpeechEMR uses AI to make medical transcription accurate and automated - IntelligentHQ

#artificialintelligence

Seoul, South Korea: SpeechEMR, an automatic voice recognition service designed by Seoul-based health-tech startup DOUB, records medical events and converts them into text data in real-time facilitating users to record medical events in a jiffy. SpeechEMR provides a high recognition rate of over 95 percent using artificial intelligence (AI) voice recognition technology specially designed for use in the medical field. Spoken audio data such as the conversations between doctors and patients or medical dictations are converted into text in real-time, through processes such as noise removal and silent syllable separation. This voice recognition service then quickly edits and saves the medical records with misspelling and omission on display coupled with correct word suggestions and medical terminology dictionary provision. Preventing information errors and improving the clarity highlights important information such as numbers, dates, units, sizes, and locations increasing the clarity and preventing sensitive information errors.


In Japan, there are some winners from the global chip shortage

The Japan Times

As the global chip shortage disrupts industries from home electronics to autos, a few small Japanese suppliers are stepping in to meeting the ballooning demand. Staying at home during the pandemic is fueling increased purchases of laptops, smartphones and games, which in turn has led to a shortage of semiconductors used in other industries. Large automakers have been forced to cut production -- globally, the sector could lose $60 billion in sales in 2021 as a result, according to IHS Markit. "Chip suppliers are doing well because orders of automotive and large household appliance chips are expanding," said Shoichi Arisawa, an analyst at Iwai Cosmo Securities Co. In addition, the auto sector is embarking on a long-term shift to add more high-performance chips for 5G wireless and autonomous driving systems.


Korea's First Space Blockbuster Just Premiered on Netflix. It's a Blast.

Slate

After a year with no new major blockbusters, Jo Sung-hee's Space Sweepers arrives as a breath of fresh air. It's not a perfect movie, nor a particularly innovative one, but the science-fiction adventure--touted as the first Korean space blockbuster--is certainly fun, with colorful performances and impressive CGI, and a worthy substitute for a new Star Wars or Marvel movie. However, its presence in a year of absences isn't the only thing that makes it noteworthy. Unlike nearly all of the movies from those two dominant franchises, Space Sweepers is led by people of color. The main characters are a crew of Koreans, and the film is one of the rare space operas that doesn't posit that English has somehow become a universal language.


SK Telecom launches 5G edge cloud service with AWS Wavelength

ZDNet

SK Telecom said on Thursday it has launched its 5G edge cloud service, called SKT 5GX Edge, embedded with Amazon Web Services (AWS) Wavelength in South Korea. The launch of the service will allow customers to build ultra-low latency mobile apps, the telco said, in areas such as machine learning, Internet of Things, gaming, and streaming. Use of the service will allow apps that are accessing the cloud to bypass the internet and regional websites, and quickly reach SK Telecom's data centre. The reduced step will allow customers to enjoy the full benefits offered by 5G network's low latency and bandwidth, the telco said. The first AWS Wavelength Zone has been launched in the city of Daejeon. It will expand to Seoul and other regions next year.


T-GAP: Learning to Walk across Time for Temporal Knowledge Graph Completion

arXiv.org Artificial Intelligence

Temporal knowledge graphs (TKGs) inherently reflect the transient nature of real-world knowledge, as opposed to static knowledge graphs. Naturally, automatic TKG completion has drawn much research interests for a more realistic modeling of relational reasoning. However, most of the existing mod-els for TKG completion extend static KG embeddings that donot fully exploit TKG structure, thus lacking in 1) account-ing for temporally relevant events already residing in the lo-cal neighborhood of a query, and 2) path-based inference that facilitates multi-hop reasoning and better interpretability. In this paper, we propose T-GAP, a novel model for TKG completion that maximally utilizes both temporal information and graph structure in its encoder and decoder. T-GAP encodes query-specific substructure of TKG by focusing on the temporal displacement between each event and the query times-tamp, and performs path-based inference by propagating attention through the graph. Our empirical experiments demonstrate that T-GAP not only achieves superior performance against state-of-the-art baselines, but also competently generalizes to queries with unseen timestamps. Through extensive qualitative analyses, we also show that T-GAP enjoys from transparent interpretability, and follows human intuition in its reasoning process.


COVID-19 Underscores the Benefits of South Korea's Artificial Intelligence Push

#artificialintelligence

The novel coronavirus is the most significant public health and economic risk that the world has faced in nearly a century. It has infected more than 65 million people and killed more than 1.5 million. The economic damage from the disruption is expected to be the worst decline in global GDP since the Great Depression. Facing a new public health and economic crisis South Korea utilized lessons from its recent experience dealing with the MERS outbreak of 2015, but also integrated artificial intelligence (AI) into its response to the COVID-19 outbreak. In early January the coronavirus was largely contained to China.


Autonomous a2z Raises US$1.9M in Seed Round for Autonomous Driving Solution

#artificialintelligence

Autonomous a2z, a member company of Born2Global Centre and Sejong Technopark, has recently received a seed investment of US$1.9 million from angel investments by individuals and partner corporations. Autonomous a2z is a company specializing in autonomous mobility solutions. The startup announced that it has begun commercializing an ongoing project. It also stated that the infusion of capital is already serving as a stepping stone for future development of autonomous mobility solutions and for assuming a leading position in relevant markets. Founded in 2018, Autonomous a2z has advanced its cutting-edge technologies to test self-driving technologies throughout Korea. As implied by its name, the firm develops "everything from a to z" in the arena of self-driving cars, including its own systems and algorithms.


Prediction for Overheating Risk Based on Deep Learning in a Zero Energy Building

#artificialintelligence

The Passive House standard has become the standard for many countries in the construction of the Zero Energy Building (ZEB). Korea also adopted the standard and has achieved great success in building energy savings. However, some issues remain with ZEBs in Korea. Among them, this study aims to discuss overheating issues. Field measurements were carried out to analyze the overheating risk for a library built as a ZEB. A data-driven overheating risk prediction model was developed to analyze the overheating risk, requiring only a small amount of data and extending the analysis throughout the year. The main factors causing overheating during both the cooling season and the intermediate seasons are also analyzed in detail. The overheating frequency exceeded 60% of days in July and August, the midsummer season in Korea. Overheating also occurred during the intermediate seasons when air conditioners were off, such as in May and October in Korea. Overheating during the cooling season was caused mainly by unexpected increases in occupancy rate, while overheating in the mid-term was mainly due to an increase in solar irradiation. This is because domestic ZEB standards define the reinforcement of insulation and airtight performance, but there are no standards for solar insolation through windows or for internal heat generation. The results of this study suggest that a fixed performance standard for ZEBs that does not reflect the climate or cultural characteristics of the region in which a ZEB is built may not result in energy savings at the operational stage and may not guarantee the thermal comfort of occupants.


Big data, machine learning shed light on Asian reforestation successes

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Since carbon sequestration is such an important factor for mitigating climate change, it's critical to understand the efficacy of reforestation efforts and develop solid estimates of forest carbon storage capacity. However, measuring forest properties can be difficult, especially in places that aren't easily reachable. Purdue University's Jingjing Liang, an assistant professor of quantitative forest ecology and co-chair of the Forest Advanced Computing and Artificial Intelligence (FACAI) Laboratory in the Department of Forestry and Natural Resources, led an international team to measure forest carbon capacity in northeast Asia. Their research, which blends remote sensing, field work and machine learning, offers the most up-to-date estimates of carbon capture potential in reclusive North Korea and details the benefits of reforestation efforts over the last two decades in China and South Korea. "Because there is historically scant data from North Korea, people know little about how much carbon is stored in this region," said Liang, whose findings were published in the journal Global Change Biology.


Research Shows How AI Can Help Reduce Opioid Use After Surgery

#artificialintelligence

According to the World Health Organization, approximately 295,000 women died during and following pregnancy and childbirth in 2017, even as maternal mortality rates have been decreasing. While every pregnancy and birth is unique, most maternal deaths are preventable. Research from the Perinatal Institute found that tracking fetal growth is essential for good prenatal care and can help prevent stillbirths when physicians are able to recognize growth restrictions. Samsung Medison and Intel are collaborating on new smart workflow solutions to improve obstetric measurements that contribute to maternal and fetal safety and can help save lives. Using an Intel Core i3 processor, the Intel Distribution of OpenVINO toolkit and OpenCV toolkit, Samsung Medison's BiometryAssist automates and simplifies fetal measurements, while LaborAssist automatically estimates the fetal angle of progression (AoP) during labor for a complete understanding of a patient's birthing progress, without the need for invasive digital vaginal exams.