Air conditioning may be factor in COVID-19 spread in the South

Harvard researchers, drawing on insights from tuberculosis research, say air conditioners may be a factor in COVID-19’s spread down South, and relatively inexpensive germicidal ultraviolet lights a weapon.

Alvin Powell • harvard
June 29, 2020 ~7 min

science-technology covid-19 coronavirus harvard-medical-school alvin-powell tb tuberculosis massachusetts-consortium-on-pathogen-readiness air-conditioning ultraviolet-light airborne-transmission edward-nardell

Harvard undergrad Michael Chen works at the corner of med and tech

Undergraduate Michael Chen, who created an extraordinary program to help treat TB, also works with a student program to treat ordinary patients.

Jill Radsken • harvard
Aug. 9, 2019 ~5 min

 biology  fas  jill-radsken  health-medicine  hms  isaac-kohane  michael-chen  tuberculosis  andrew-beam  applied-math  biomedical-informatics-lab  crimson-care-collaborative  maha-farhat  medical-technology  sean-eddy

Harvard undergrad’s AI model helps to predict TB resistance

A Harvard undergrad, working with Harvard Medical School scientists, has designed an artificial intelligence model that predicts tuberculosis resistance to 10 most commonly used drugs. The new model outperforms previous machine-learning tools, and incorporating it into clinical tests could dramatically enhance early detection and prompt treatment of drug-resistant TB.

Ekaterina Pesheva • harvard
May 2, 2019 ~11 min

 science-technology  harvard-medical-school  hms  blavatnik-institute  harvard-th-chan-school-of-public-health  massachusetts-general-hospital  mgh  akshith-doddi  analysis-group  andy-beam  bill-and-melinda-gates-foundation  critical-path-institute  drug-resistance  ebiomedicine  gentb  isaac-kohane  jimmy-royer  luca-freschi  marco-schito  masha-farhat  matthew-ezewudo  mdr-tb  michael-chen  tb  tuberculosis  university-of-virginia-school-of-medicine  xdr-tb

Harvard undergrad’s AI model predicts TB resistance

A Harvard undergrad, working with Harvard Medical School scientists, has designed an artificial intelligence model that predicts tuberculosis resistance to 10 most commonly used drugs. The new model outperforms previous machine-learning tools, and incorporating it into clinical tests could dramatically enhance early detection and prompt treatment of drug-resistant TB.

Ekaterina Pesheva • harvard
May 2, 2019 ~11 min

 science-technology  harvard-medical-school  hms  blavatnik-institute  harvard-th-chan-school-of-public-health  massachusetts-general-hospital  mgh  akshith-doddi  analysis-group  andy-beam  bill-and-melinda-gates-foundation  critical-path-institute  drug-resistance  ebiomedicine  gentb  isaac-kohane  jimmy-royer  luca-freschi  marco-schito  masha-farhat  matthew-ezewudo  mdr-tb  michael-chen  tb  tuberculosis  university-of-virginia-school-of-medicine  xdr-tb

/

1