| Img Medical Group Nj, P.a. | |
|
201 Broad St Ste 420 Stamford CT 06901-2004 | |
| (917) 334-9589 | |
| Not Available |
| Full Name | Img Medical Group Nj, P.a. |
|---|---|
| Speciality | Internal Medicine |
| Location | 201 Broad St Ste 420, Stamford, Connecticut |
| Authorized Official Name and Position | Robert Refowitz (PRESIDENT) |
| Authorized Official Contact | 9173349589 |
| Accepts Medicare Insurance | This clinic does not participate in Medicare Program. |
| Mailing Address | Practice Location Address |
|---|---|
| Img Medical Group Nj, P.a. 201 Broad St Ste 420 Stamford CT 06901-2004 Ph: (917) 334-9589 | Img Medical Group Nj, P.a. 201 Broad St Ste 420 Stamford CT 06901-2004 Ph: (917) 334-9589 |
| NPI Number | 1174205306 |
|---|---|
| Provider Enumeration Date | 08/07/2023 |
| Last Update Date | 08/07/2023 |
| Identifier | Type | State | Issuer |
|---|---|---|---|
| 1174205306 | NPI | - | NPPES |
| Taxonomy | Type | License (State) | Status |
|---|---|---|---|
| 207R00000X | Internal Medicine | (* (Not Available)) | Primary |
News Archive
A new study in CMAJ (Canadian Medical Association Journal) http://www.cmaj.ca/cgi/doi/10.1503/cmaj.091823 of all patients in Canada admitted to hospital for H1N1 in the first five months of the outbreak summarizes the risk factors for a severe outcome (www.cmaj.ca). The H1N1 pandemic presents important learnings for clinicians and researchers and data on severe outcomes can help inform future treatment and prevention guidelines.
Ten million people in the United States are estimated to already have bone diseases, and almost 34 million more are estimated to have low bone mass, putting them at increased risk for osteoporosis, according to the National Osteoporosis Foundation.
Writing in the May 28 issue of Cell, Johns Hopkins researchers report that four critical components of cells' protein-building machine don't do what scientists had long assumed.
The advent of electronic medical records with large image databases, along with advances in artificial intelligence with deep learning, is offering medical professionals new opportunities to dramatically improve image analysis and disease diagnostics.
Knowing the stage of a patient's melanoma is important when choosing the best course of treatment. When the cancer has progressed to the lymph nodes, a more aggressive treatment is needed. Examining an entire lymph node for cancer takes much effort and time; a new technique might help make the process more efficient.
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